diff --git a/.github/workflows/build_package.yml b/.github/workflows/build_package.yml
index b1d319f..990090e 100644
--- a/.github/workflows/build_package.yml
+++ b/.github/workflows/build_package.yml
@@ -9,7 +9,7 @@ jobs:
     strategy:
       matrix:
         os: [macos-latest, ubuntu-latest, windows-latest]
-        python: ["3.9", "3.10"]
+        python: ["3.11", "3.12"]
 
     steps:
       - uses: actions/checkout@v4
diff --git a/.github/workflows/publish_docs.yml b/.github/workflows/publish_docs.yml
index 5bcbb6d..4a48197 100644
--- a/.github/workflows/publish_docs.yml
+++ b/.github/workflows/publish_docs.yml
@@ -13,7 +13,7 @@ jobs:
       - name: Setup Python
         uses: actions/setup-python@v5
         with:
-          python-version: 3.9
+          python-version: 3.11
 
       - name: Install pip
         run: |
diff --git a/.github/workflows/run_tests.yml b/.github/workflows/run_tests.yml
index 65a296f..4a4eaca 100644
--- a/.github/workflows/run_tests.yml
+++ b/.github/workflows/run_tests.yml
@@ -16,14 +16,14 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - { python-version: "3.10", os: ubuntu-latest, session: "pre-commit" }
-          - { python-version: "3.10", os: ubuntu-latest, session: "safety" }
-          - { python-version: "3.10", os: ubuntu-latest, session: "mypy" }
-          - { python-version: "3.10", os: ubuntu-latest, session: "tests" }
-          - { python-version: "3.10", os: windows-latest, session: "tests" }
-          - { python-version: "3.10", os: ubuntu-latest, session: "typeguard" }
-          - { python-version: "3.10", os: ubuntu-latest, session: "xdoctest" }
-          - { python-version: "3.10", os: ubuntu-latest, session: "docs-build" }
+          - { python-version: "3.11", os: ubuntu-latest, session: "pre-commit" }
+          - { python-version: "3.11", os: ubuntu-latest, session: "safety" }
+          - { python-version: "3.11", os: ubuntu-latest, session: "mypy" }
+          - { python-version: "3.11", os: ubuntu-latest, session: "tests" }
+          - { python-version: "3.11", os: windows-latest, session: "tests" }
+          - { python-version: "3.11", os: ubuntu-latest, session: "typeguard" }
+          - { python-version: "3.11", os: ubuntu-latest, session: "xdoctest" }
+          - { python-version: "3.11", os: ubuntu-latest, session: "docs-build" }
 
     env:
       NOXSESSION: ${{ matrix.session }}
diff --git a/docs/API.rst b/docs/API.rst
deleted file mode 100644
index cb55f7e..0000000
--- a/docs/API.rst
+++ /dev/null
@@ -1,29 +0,0 @@
-.. module:: drevalpy
-
-.. automodule:: drevalpy
-   :noindex:
-
-API
-===
-
-Import DrEvalPy using
-
-.. code-block:: python
-
-   import drevalpy as dep
-
-..
-   Models module: :code:`models`
-   -------------------------
-
-   .. module:: devalpy.models
-
-   .. currentmodule:: drevalpy
-
-   Available models
-   ~~~~~~~~~~~~~~~~
-
-   .. autosummary::
-      :toctree: api/models
-
-      models.baselines
\ No newline at end of file
diff --git a/docs/conf.py b/docs/conf.py
index 491b879..75cc372 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -16,9 +16,7 @@
 
 from jinja2.defaults import DEFAULT_FILTERS
 
-import drevalpy
-
-sys.path.insert(0, os.path.abspath("../"))
+sys.path.insert(0, os.path.abspath(".."))
 
 
 # -- General configuration ---------------------------------------------
@@ -58,9 +56,9 @@
 # the built documents.
 #
 # The short X.Y version.
-version = drevalpy.__version__
+version = "1.0.10"
 # The full version, including alpha/beta/rc tags.
-release = drevalpy.__version__
+release = "1.0.10"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
diff --git a/docs/requirements.txt b/docs/requirements.txt
index 521aa7c..9cd98f2 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,5 +1,4 @@
-sphinx-autobuild==2024.10.3 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-sphinx-autodoc-typehints==2.3.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-sphinx-click==6.0.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-sphinx-rtd-theme==3.0.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
--e .
+sphinx-autobuild==2024.10.3 ; python_version >= "3.11" and python_version < "3.13"
+sphinx-autodoc-typehints==2.5.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinx-click==6.0.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinx-rtd-theme==3.0.2 ; python_version >= "3.11" and python_version < "3.13"
diff --git a/drevalpy/datasets/curvecurator.py b/drevalpy/datasets/curvecurator.py
new file mode 100644
index 0000000..f6ed52e
--- /dev/null
+++ b/drevalpy/datasets/curvecurator.py
@@ -0,0 +1,224 @@
+"""
+Contains all function required for CurveCurator fitting.
+
+CurveCurator publication:
+Bayer, F.P., Gander, M., Kuster, B. et al. CurveCurator: a recalibrated F-statistic to assess,
+classify, and explore significance of dose–response curves. Nat Commun 14, 7902 (2023).
+https://doi-org.eaccess.tum.edu/10.1038/s41467-023-43696-z
+
+CurveCurator applies a recalibrated F-statistic for p-value estimation of 4-point log-logistic
+regression fits. In drevalpy, this can be used to generate training data with higher quality, since
+quality measures, such as p-value, R2, or relevance score can be used to filter out viability
+measurements of low quality.
+"""
+
+import subprocess
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+import toml
+
+from ..pipeline_function import pipeline_function
+
+
+def _prepare_raw_data(curve_df: pd.DataFrame, output_dir: str | Path):
+    required_columns = ["dose", "response", "sample", "drug"]
+    if not all([col in curve_df.columns for col in required_columns]):
+        raise ValueError("Missing columns in viability data. Required columns are {required_columns}.")
+    if "replicate" in curve_df.columns:
+        required_columns.append("replicate")
+    curve_df = curve_df[required_columns]
+    n_replicates = 1
+    conc_columns = ["dose"]
+    has_multicol_index = False
+    if "replicate" in curve_df.columns:
+        n_replicates = curve_df["replicate"].nunique()
+        conc_columns.append("replicate")
+        has_multicol_index = True
+
+    df = curve_df.pivot(index=["sample", "drug"], columns=conc_columns, values="response")
+
+    for i in range(n_replicates):
+        df.insert(0, (0.0, n_replicates - i), 1.0)
+
+    concentrations = df.columns.sort_values()
+    df = df[concentrations]
+
+    experiments = np.arange(df.shape[1])
+    df.insert(0, "Name", df.index.map(lambda x: f"{x[0]}|{x[1]}"))
+    df.columns = ["Name"] + [f"Raw {i}" for i in experiments]
+
+    curvecurator_folder = Path(output_dir)
+    curvecurator_folder.mkdir(exist_ok=True, parents=True)
+    df.to_csv(curvecurator_folder / "curvecurator_input.tsv", sep="\t", index=False)
+
+    if has_multicol_index:
+        doses = [pair[0] for pair in concentrations]
+    else:
+        doses = concentrations.to_list()
+    return len(experiments), doses, n_replicates, len(df)
+
+
+def _prepare_toml(filename: str, n_exp: int, n_replicates: int, doses: list[float], dataset_name: str, cores: int):
+    config = {
+        "Meta": {
+            "id": filename,
+            "description": dataset_name,
+            "condition": "drug",
+            "treatment_time": "72 h",
+        },
+        "Experiment": {
+            "experiments": range(n_exp),
+            "doses": doses,
+            "dose_scale": "1e-06",
+            "dose_unit": "M",
+            "control_experiment": [i for i in range(n_replicates)],
+            "measurement_type": "OTHER",
+            "data_type": "OTHER",
+            "search_engine": "OTHER",
+            "search_engine_version": "0",
+        },
+        "Paths": {
+            "input_file": "curvecurator_input.tsv",
+            "curves_file": "curves.txt",
+            "normalization_file": "norm.txt",
+            "mad_file": "mad.txt",
+            "dashboard": "dashboard.html",
+        },
+        "Processing": {
+            "available_cores": cores,
+            "max_missing": max(len(doses) - 5, 0),
+            "imputation": False,
+            "normalization": False,
+        },
+        "Curve Fit": {
+            "type": "OLS",
+            "speed": "exhaustive",
+            "max_iterations": 1000,
+            "interpolation": False,
+            "control_fold_change": True,
+        },
+        "F Statistic": {
+            "optimized_dofs": True,
+            "alpha": 0.05,
+            "fc_lim": 0.45,
+        },
+    }
+    return config
+
+
+def _exec_curvecurator(output_dir: Path):
+    command = ["CurveCurator", str(output_dir / "config.toml"), "--mad"]
+    process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    process.communicate()
+
+
+def _calc_ic50(model_params_df: pd.DataFrame):
+    """
+    Calculate the IC50 from a fitted model.
+
+    This function expects a dataframe that was processed in the postprocess function, containing
+    the columns "Front", "Back", "Slope", "pEC50". It calculates the IC50 for all the models in the
+    dataframe in closed form and adds the column IC50_curvecurator to the input dataframe.
+
+    :param model_params_df: a dataframe containing the fitted parameters
+    """
+
+    def ic50(front, back, slope, pec50):
+        return (np.log10((front - back) / (0.5 + back)) - slope * pec50) / slope
+
+    front = model_params_df["Front"].values
+    back = model_params_df["Back"].values
+    slope = model_params_df["Slope"].values
+    pec50 = model_params_df["pEC50"].values
+
+    model_params_df["IC50_curvecurator"] = ic50(front, back, slope, pec50)
+
+
+@pipeline_function
+def preprocess(input_file: str | Path, output_dir: str | Path, dataset_name: str, cores: int):
+    """
+    Preprocess raw viability data and create config.toml for use with CurveCurator.
+
+    :param input_file: Path to csv file containing the raw viability data
+    :param output_dir: Path to store all the files to, including the preprocessed data, the config.toml
+        for CurveCurator, CurveCurator's output files, and the postprocessed data
+    :param dataset_name: Name of the dataset
+    :param cores: The number of cores to be used for fitting the curves using CurveCurator.
+        This parameter is written into the config.toml, but it is min of the number of curves to fit
+        and the number given (min(n_curves, cores))
+    """
+    input_file = Path(input_file)
+    output_dir = Path(output_dir)
+    curve_df = pd.read_csv(input_file)
+
+    n_exp, doses, n_replicates, n_curves_to_fit = _prepare_raw_data(curve_df, output_dir)
+    cores = min(n_curves_to_fit, cores)
+
+    config = _prepare_toml(input_file.name, n_exp, n_replicates, doses, dataset_name, cores)
+    with open(output_dir / "config.toml", "w") as f:
+        toml.dump(config, f)
+
+
+@pipeline_function
+def postprocess(output_folder: str | Path, dataset_name: str):
+    """
+    Postprocess CurveCurator output file.
+
+    This function reads the curves.txt file created by CurveCurator, which contains the
+    fitted curve parameters and postprocesses it to be used by drevalpy.
+
+    :param output_folder: Path to the output folder of CurveCurator containin the curves.txt file.
+    :param dataset_name: The name of the dataset, will be used to prepend the postprocessed <dataset_name>.csv file
+    """
+    output_folder = Path(output_folder)
+    required_columns = {
+        "Name": "Name",
+        "pEC50": "pEC50",
+        "pEC50 Error": "pEC50Error",
+        "Curve Slope": "Slope",
+        "Curve Front": "Front",
+        "Curve Back": "Back",
+        "Curve Fold Change": "FoldChange",
+        "Curve AUC": "AUC",
+        "Curve R2": "R2",
+        "Curve P_Value": "pValue",
+        "Curve Relevance Score": "RelevanceScore",
+        "Curve F_Value": "fValue",
+        "Curve Log P_Value": "negLog10pValue",
+        "Signal Quality": "SignalQuality",
+        "Curve RMSE": "RMSE",
+        "Curve F_Value SAM Corrected": "fValueSAMCorrected",
+        "Curve Regulation": "Regulation",
+    }
+    fitted_curve_data = pd.read_csv(Path(output_folder) / "curves.txt", sep="\t", usecols=required_columns).rename(
+        columns=required_columns
+    )
+    fitted_curve_data[["cell_line_id", "drug_id"]] = fitted_curve_data.Name.str.split("|", expand=True)
+    fitted_curve_data["EC50_curvecurator"] = np.power(
+        10, -fitted_curve_data["pEC50"].values
+    )  # in CurveCurator 10^-pEC50 = EC50
+    _calc_ic50(fitted_curve_data)
+    fitted_curve_data.to_csv(output_folder / f"{dataset_name}.csv", index=None)
+
+
+def fit_curves(input_file: str | Path, output_dir: str | Path, dataset_name: str, cores: int):
+    """
+    Fit curves for provided raw viability data.
+
+    This functions reads viability data in a predefined input format, preprocesses the data
+    to be readable by CurveCurator, fits curves to the data using CurveCurator, and postprocesses
+    the fitted data to a format required by drevalpy.
+
+    :param input_file: Path to the file containing the raw viability data
+    :param output_dir: Path to store all the files to, including the preprocessed data, the config.toml
+        for CurveCurator, CurveCurator's output files, and the postprocessed data
+    :param dataset_name: The name of the dataset, will be used to prepend the postprocessed <dataset_name>.csv file
+    :param cores: The number of cores to be used for fitting the curves using CurveCurator.
+        This parameter is written into the config.toml, but it is min of the number of curves to fit
+        and the number given (min(n_curves, cores))
+    """
+    preprocess(input_file, output_dir, dataset_name, cores)
+    _exec_curvecurator(Path(output_dir))
+    postprocess(output_dir, dataset_name)
diff --git a/drevalpy/datasets/dataset.py b/drevalpy/datasets/dataset.py
index 394c438..528e8f6 100644
--- a/drevalpy/datasets/dataset.py
+++ b/drevalpy/datasets/dataset.py
@@ -66,7 +66,10 @@ class DrugResponseDataset(Dataset):
 
     @classmethod
     def from_csv(
-        cls: type["DrugResponseDataset"], input_file: str | Path, dataset_name: str = "unknown"
+        cls: type["DrugResponseDataset"],
+        input_file: str | Path,
+        dataset_name: str = "unknown",
+        measure: str = "response",
     ) -> "DrugResponseDataset":
         """
         Load a dataset from a csv file.
@@ -80,6 +83,7 @@ def from_csv(
 
         :param input_file: Path to the csv file containing the data to be loaded
         :param dataset_name: Optional name to associate the dataset with, default = "unknown"
+        :param measure: The name of the column containing the measure to predict, default = "response"
 
         :returns: DrugResponseDataset object containing data from provided csv file.
         """
@@ -89,7 +93,7 @@ def from_csv(
         else:
             predictions = None
         return cls(
-            response=data["response"].values,
+            response=data[measure].values,
             cell_line_ids=data["cell_line_id"].values,
             drug_ids=data["drug_id"].values,
             predictions=predictions,
diff --git a/drevalpy/datasets/loader.py b/drevalpy/datasets/loader.py
index 396d32a..8ad8055 100644
--- a/drevalpy/datasets/loader.py
+++ b/drevalpy/datasets/loader.py
@@ -1,23 +1,30 @@
 """Contains functions to load the GDSC1, GDSC2, CCLE, and Toy datasets."""
 
 import os
+from pathlib import Path
 from typing import Callable
 
 import pandas as pd
 
 from ..pipeline_function import pipeline_function
+from .curvecurator import fit_curves
 from .dataset import DrugResponseDataset
 from .utils import download_dataset
 
 
 def load_gdsc1(
-    path_data: str = "data", file_name: str = "response_GDSC1.csv", dataset_name: str = "GDSC1"
+    path_data: str = "data",
+    measure: str = "LN_IC50",
+    file_name: str = "response_GDSC1.csv",
+    dataset_name: str = "GDSC1",
 ) -> DrugResponseDataset:
     """
     Loads the GDSC1 dataset.
 
     :param path_data: Path to the dataset.
     :param file_name: File name of the dataset.
+    :param measure: The name of the column containing the measure to predict, default = "LN_IC50"
+
     :param dataset_name: Name of the dataset.
     :return: DrugResponseDataset containing response, cell line IDs, and drug IDs.
     """
@@ -29,30 +36,36 @@ def load_gdsc1(
     response_data["DRUG_NAME"] = response_data["DRUG_NAME"].str.replace(",", "")
 
     return DrugResponseDataset(
-        response=response_data["LN_IC50"].values,
+        response=response_data[measure].values,
         cell_line_ids=response_data["CELL_LINE_NAME"].values,
         drug_ids=response_data["DRUG_NAME"].values,
         dataset_name=dataset_name,
     )
 
 
-def load_gdsc2(path_data: str = "data", file_name: str = "response_GDSC2.csv"):
+def load_gdsc2(path_data: str = "data", measure: str = "LN_IC50", file_name: str = "response_GDSC2.csv"):
     """
     Loads the GDSC2 dataset.
 
     :param path_data: Path to the dataset.
     :param file_name: File name of the dataset.
+    :param measure: The name of the column containing the measure to predict, default = "LN_IC50"
+
     :return: DrugResponseDataset containing response, cell line IDs, and drug IDs.
     """
-    return load_gdsc1(path_data=path_data, file_name=file_name, dataset_name="GDSC2")
+    return load_gdsc1(path_data=path_data, measure=measure, file_name=file_name, dataset_name="GDSC2")
 
 
-def load_ccle(path_data: str = "data", file_name: str = "response_CCLE.csv") -> DrugResponseDataset:
+def load_ccle(
+    path_data: str = "data", measure: str = "LN_IC50", file_name: str = "response_CCLE.csv"
+) -> DrugResponseDataset:
     """
     Loads the CCLE dataset.
 
     :param path_data: Path to the dataset.
     :param file_name: File name of the dataset.
+    :param measure: The name of the column containing the measure to predict, default = "LN_IC50"
+
     :return: DrugResponseDataset containing response, cell line IDs, and drug IDs.
     """
     dataset_name = "CCLE"
@@ -64,34 +77,49 @@ def load_ccle(path_data: str = "data", file_name: str = "response_CCLE.csv") ->
     response_data["DRUG_NAME"] = response_data["DRUG_NAME"].str.replace(",", "")
 
     return DrugResponseDataset(
-        response=response_data["LN_IC50"].values,
+        response=response_data[measure].values,
         cell_line_ids=response_data["CELL_LINE_NAME"].values,
         drug_ids=response_data["DRUG_NAME"].values,
         dataset_name=dataset_name,
     )
 
 
-def load_toy(path_data: str = "data") -> DrugResponseDataset:
+def load_toy(path_data: str = "data", measure: str = "response") -> DrugResponseDataset:
     """
     Loads small Toy dataset, subsampled from GDSC1.
 
     :param path_data: Path to the dataset.
+    :param measure: The name of the column containing the measure to predict, default = "response"
+
     :return: DrugResponseDataset containing response, cell line IDs, and drug IDs.
     """
     dataset_name = "Toy_Data"
+    measure = "response"  # overwrite this explicitly to avoid problems, should be changed in the future
     path = os.path.join(path_data, dataset_name, "toy_data.csv")
     if not os.path.exists(path):
         download_dataset(dataset_name, path_data, redownload=True)
     response_data = pd.read_csv(path)
 
     return DrugResponseDataset(
-        response=response_data["response"].values,
+        response=response_data[measure].values,
         cell_line_ids=response_data["cell_line_id"].values,
         drug_ids=response_data["drug_id"].values,
         dataset_name=dataset_name,
     )
 
 
+def load_custom(path_data: str | Path, measure: str = "response") -> DrugResponseDataset:
+    """
+    Load custom dataset.
+
+    :param path_data: Path to location of custom dataset
+    :param measure: The name of the column containing the measure to predict, default = "response"
+
+    :return: DrugResponseDataset containing response, cell line IDs, and drug IDs
+    """
+    return DrugResponseDataset.from_csv(path_data, measure=measure)
+
+
 AVAILABLE_DATASETS: dict[str, Callable] = {
     "GDSC1": load_gdsc1,
     "GDSC2": load_gdsc2,
@@ -101,16 +129,45 @@ def load_toy(path_data: str = "data") -> DrugResponseDataset:
 
 
 @pipeline_function
-def load_dataset(dataset_name: str, path_data: str = "data") -> DrugResponseDataset:
+def load_dataset(
+    dataset_name: str, path_data: str = "data", measure: str = "response", curve_curator: bool = False, cores: int = 1
+) -> DrugResponseDataset:
     """
     Load a dataset based on the dataset name.
 
-    :param dataset_name: The name of the dataset to load ('GDSC1', 'GDSC2', 'CCLE', or 'Toy_Data').
-    :param path_data: The path to the dataset.
+    :param dataset_name: The name of the dataset to load. Can be one of ('GDSC1', 'GDSC2', 'CCLE', or 'Toy_Data')
+        to download provided datasets, or any other name to allow for custom datasets.
+    :param path_data: The parent path in which custom or downloaded datasets should be located, or in which raw
+        viability data is to be found for fitting with CurveCurator (see param curve_curator for details).
+        The location of the datasets are resolved by <path_data>/<dataset_name>/<dataset_name>.csv.
+    :param measure: The name of the column containing the measure to predict, default = "response".
+        If curve_curator is True, this measure is appended with "_curvecurator", e.g. "response_curvecurator" to
+        distinguish between measures provided by the original source of a dataset, or the measures fit by
+        CurveCurator.
+    :param curve_curator: If True, the measure is appended with "_curvecurator".
+        If a custom dataset_name was provided, this will invoke the fitting procedure of raw viability data,
+        which is expected to exist at <path_data>/<dataset_name>/<dataset_name>_raw.csv. The fitted dataset will
+        be stored in the same folder, in a file called <dataset_name>.csv
+    :param cores: Number of cores to use for CurveCurator fitting. Only used when curve_curator is True, default = 1
     :return: A DrugResponseDataset containing response, cell line IDs, drug IDs, and dataset name.
-    :raises ValueError: If the dataset name is unknown.
+    :raises FileNotFoundError: If the custom dataset or raw viability data could not be found at the given path.
     """
-    if dataset_name in AVAILABLE_DATASETS:
-        return AVAILABLE_DATASETS[dataset_name](path_data)  # type: ignore
+    if curve_curator:
+        measure += "_curvecurator"
+        input_file = Path(path_data) / dataset_name / f"{dataset_name}_raw.csv"
     else:
-        raise ValueError(f"Unknown dataset name: {dataset_name}")
+        input_file = Path(path_data) / dataset_name / f"{dataset_name}.csv"
+
+    if dataset_name in AVAILABLE_DATASETS:
+        return AVAILABLE_DATASETS[dataset_name](path_data, measure)  # type: ignore
+
+    if input_file.is_file():
+        if curve_curator:
+            fit_curves(
+                input_file=input_file,
+                output_dir=input_file.parent,
+                dataset_name=dataset_name,
+                cores=cores,
+            )
+        return load_custom(Path(path_data) / dataset_name / f"{dataset_name}.csv", measure=measure)
+    raise FileNotFoundError(f"Custom dataset does not exist at given path: {input_file}")
diff --git a/drevalpy/utils.py b/drevalpy/utils.py
index a4c7df7..0962407 100644
--- a/drevalpy/utils.py
+++ b/drevalpy/utils.py
@@ -126,6 +126,21 @@ def get_parser() -> argparse.ArgumentParser:
         default=False,
         help="Whether to run " "CurveCurator " "to sort out " "non-reactive " "curves",
     )
+
+    parser.add_argument(
+        "--curve_curator_cores",
+        type=int,
+        default=1,
+        help="Max. number of cores used to fit curves with CurveCurator following min(cores, #curves to fit).",
+    )
+
+    parser.add_argument(
+        "--measure",
+        type=str,
+        default="LN_IC50",
+        help="The drug response measure used as prediction target. Can be one of ['LN_IC50', 'response']",
+    )
+
     parser.add_argument(
         "--overwrite",
         action="store_true",
@@ -170,8 +185,7 @@ def check_arguments(args) -> None:
 
     :param args: arguments passed from the command line
     :raises AssertionError: if any of the arguments is invalid
-    :raises NotImplementedError: because CurveCurator is not implemented yet
-    :raises ValueError: if the number of cross-validation splits is less than 1
+    :raises ValueError: if the number of cross-validation splits or curve_curator_cores is less than 1
     """
     if not args.models:
         raise AssertionError("At least one model must be specified")
@@ -212,7 +226,7 @@ def check_arguments(args) -> None:
     os.makedirs(args.path_data, exist_ok=True)
 
     if args.n_cv_splits <= 1:
-        raise ValueError("Number of cross-validation splits must be greater than 1")
+        raise ValueError("Number of cross-validation splits must be greater than 1.")
 
     # TODO Allow for custom randomization tests maybe via config file
     if args.randomization_mode[0] != "None":
@@ -221,9 +235,15 @@ def check_arguments(args) -> None:
                 "At least one invalid randomization mode. Available randomization modes are SVCC, " "SVRC, SVSC, SVRD"
             )
     if args.curve_curator:
-        raise NotImplementedError("CurveCurator not implemented")
+        if args.curve_curator_cores < 1:
+            raise ValueError("Number of cores for CurveCurator must be greater than 0.")
+
+    if args.measure not in ["LN_IC50", "response"]:
+        raise ValueError("Only 'LN_IC50' and 'response' are currently available as a drug response measure.")
+
     if args.response_transformation not in ["None", "standard", "minmax", "robust"]:
         raise AssertionError("Invalid response_transformation. Choose from None, standard, minmax, robust")
+
     if args.optim_metric not in AVAILABLE_METRICS:
         raise AssertionError(
             f"Invalid optim_metric for hyperparameter tuning. Choose from" f" {list(AVAILABLE_METRICS.keys())}"
@@ -243,6 +263,9 @@ def main(args) -> None:
         dataset_name=args.dataset_name,
         cross_study_datasets=args.cross_study_datasets,
         path_data=args.path_data,
+        measure=args.measure,
+        curve_curator=args.curve_curator,
+        cores=args.curve_curator_cores,
     )
 
     models = [MODEL_FACTORY[model] for model in args.models]
@@ -279,20 +302,43 @@ def main(args) -> None:
 
 
 def get_datasets(
-    dataset_name: str, cross_study_datasets: list, path_data: str = "data"
+    dataset_name: str,
+    cross_study_datasets: list,
+    path_data: str = "data",
+    measure: str = "response",
+    curve_curator: bool = False,
+    cores: int = 1,
 ) -> tuple[DrugResponseDataset, Optional[list[DrugResponseDataset]]]:
     """
     Load the response data and cross-study datasets.
 
-    :param dataset_name: name of the dataset
-    :param cross_study_datasets: list of cross-study datasets
-    :param path_data: path to the data directory, default is "data"
+    :param dataset_name: The name of the dataset to load. Can be one of ('GDSC1', 'GDSC2', 'CCLE', or 'Toy_Data')
+        to download provided datasets, or any other name to allow for custom datasets.
+    :param cross_study_datasets: list of cross-study datasets. CurveCurator is not applicable to these. If you wish
+        to provide custom cross_study_datasets, you have to invoke curve fitting manually using
+        drevalpy.datasets.curvecurator.fit_curves
+    :param path_data: The parent path in which custom or downloaded datasets should be located, or in which raw
+        viability data is to be found for fitting with CurveCurator (see param curve_curator for details).
+        The location of the datasets are resolved by <path_data>/<dataset_name>/<dataset_name>.csv.
+    :param measure: The name of the column containing the measure to predict, default = "response".
+        If curve_curator is True, this measure is appended with "_curvecurator", e.g. "response_curvecurator" to
+        distinguish between measures provided by the original source of a dataset, or the measures fit by
+        CurveCurator.
+    :param curve_curator: If True, the measure is appended with "_curvecurator".
+        If a custom dataset_name was provided, this will invoke the fitting procedure of raw viability data,
+        which is expected to exist at <path_data>/<dataset_name>/<dataset_name>_raw.csv. The fitted dataset will
+        be stored in the same folder, in a file called <dataset_name>.csv
+    :param cores: Number of cores to use for CurveCurator fitting. Only used when curve_curator is True, default = 1
     :returns: response data and, potentially, cross-study datasets
     """
     # PIPELINE: LOAD_RESPONSE
-    response_data = load_dataset(dataset_name=dataset_name, path_data=path_data)
+    response_data = load_dataset(
+        dataset_name=dataset_name, path_data=path_data, measure=measure, curve_curator=curve_curator, cores=cores
+    )
 
-    cross_study_datasets = [load_dataset(dataset_name=dn, path_data=path_data) for dn in cross_study_datasets]
+    cross_study_datasets = [
+        load_dataset(dataset_name=dn, path_data=path_data, measure=measure) for dn in cross_study_datasets
+    ]
     return response_data, cross_study_datasets
 
 
diff --git a/noxfile.py b/noxfile.py
index fc5cb95..dfc9e41 100644
--- a/noxfile.py
+++ b/noxfile.py
@@ -18,7 +18,7 @@
     sys.exit(1)
 
 package = "drevalpy"
-python_versions = ["3.10", "3.11"]
+python_versions = ["3.11", "3.12"]
 nox.options.sessions = (
     "pre-commit",
     "safety",
@@ -147,7 +147,7 @@ def mypy(session: Session) -> None:
     """
     args = session.posargs or ["drevalpy", "tests", "docs/conf.py"]
     session.install(".")
-    session.install("mypy", "pytest", "types-requests", "types-attrs", "types-PyYAML")
+    session.install("mypy", "pytest", "types-requests", "types-attrs", "types-PyYAML", "types-toml")
     session.run("mypy", *args)
 
 
@@ -158,7 +158,7 @@ def tests(session: Session) -> None:
 
     :param session: The Session object.
     """
-    session.install(".")
+    session.install(".[fit]")
     session.install("coverage[toml]", "pytest", "pygments")
     try:
         session.run("coverage", "run", "--parallel", "-m", "pytest", *session.posargs)
@@ -194,7 +194,7 @@ def typeguard(session: Session) -> None:
 
     :param session: The Session object.
     """
-    session.install(".")
+    session.install(".[fit]")
     session.install("pytest", "typeguard", "pygments")
     session.run("pytest", f"--typeguard-packages={package}", *session.posargs)
 
diff --git a/poetry.lock b/poetry.lock
index ee14f42..68a21fe 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,93 +13,92 @@ files = [
 
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+version = "3.11.7"
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 ]
 
 [package.dependencies]
 aiohappyeyeballs = ">=2.3.0"
 aiosignal = ">=1.1.2"
-async-timeout = {version = ">=4.0,<6.0", markers = "python_version < \"3.11\""}
 attrs = ">=17.3.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
@@ -125,13 +124,13 @@ frozenlist = ">=1.1.0"
 
 [[package]]
 name = "alabaster"
-version = "0.7.16"
+version = "1.0.0"
 description = "A light, configurable Sphinx theme"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 files = [
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@@ -146,10 +145,8 @@ files = [
 ]
 
 [package.dependencies]
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 idna = ">=2.8"
 sniffio = ">=1.1"
-typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
@@ -170,17 +167,6 @@ files = [
 [package.extras]
 test = ["coverage", "mypy", "pexpect", "ruff", "wheel"]
 
-[[package]]
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-optional = false
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 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
+[[package]]
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+description = "Interactive plots and applications in the browser from Python"
+optional = true
+python-versions = ">=3.9"
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+packaging = ">=16.8"
+pandas = ">=1.2"
+pillow = ">=7.1.0"
+PyYAML = ">=3.10"
+tornado = ">=6.2"
+xyzservices = ">=2021.09.1"
+
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 version = "2024.8.30"
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 ]
 
 [package.dependencies]
@@ -546,6 +541,25 @@ mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.11.1)", "types-Pil
 test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
 test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"]
 
+[[package]]
+name = "curve-curator"
+version = "0.5.1"
+description = "CurveCurator is an open-source analysis platform for any dose-dependent data. It fits a classical 4-parameter equation to estimate effect potency, effect size, and the statistical significance of the observed response. 2D-thresholding efficiently reduces false positives in high-throughput experiments and separates relevant from irrelevant or insignificant hits in an automated and unbiased manner. An interactive dashboard allows users to quickly explore data locally."
+optional = true
+python-versions = "<3.13,>=3.11"
+files = [
+    {file = "curve_curator-0.5.1-py3-none-any.whl", hash = "sha256:23b74f7c92f1cc9bd0fdedb3429514df4b779fa39a98dfe5eb4ae14efb67b0ee"},
+]
+
+[package.dependencies]
+bokeh = ">=3.4.0,<3.5.0"
+numpy = ">=1.25.0,<2.0.0"
+pandas = ">=2.1.2,<3.0.0"
+pytest = ">=7.4.3,<8.0.0"
+scipy = ">=1.10.1,<2.0.0"
+statsmodels = ">=0.14.0,<0.15.0"
+tqdm = ">=4.66.1,<5.0.0"
+
 [[package]]
 name = "cycler"
 version = "0.12.1"
@@ -594,20 +608,6 @@ files = [
     {file = "docutils-0.21.2.tar.gz", hash = "sha256:3a6b18732edf182daa3cd12775bbb338cf5691468f91eeeb109deff6ebfa986f"},
 ]
 
-[[package]]
-name = "exceptiongroup"
-version = "1.2.2"
-description = "Backport of PEP 654 (exception groups)"
-optional = false
-python-versions = ">=3.7"
-files = [
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-]
-
-[package.extras]
-test = ["pytest (>=6)"]
-
 [[package]]
 name = "filelock"
 version = "3.16.1"
@@ -947,13 +947,13 @@ files = [
 
 [[package]]
 name = "identify"
-version = "2.6.2"
+version = "2.6.3"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "identify-2.6.2-py2.py3-none-any.whl", hash = "sha256:c097384259f49e372f4ea00a19719d95ae27dd5ff0fd77ad630aa891306b82f3"},
-    {file = "identify-2.6.2.tar.gz", hash = "sha256:fab5c716c24d7a789775228823797296a2994b075fb6080ac83a102772a98cbd"},
+    {file = "identify-2.6.3-py2.py3-none-any.whl", hash = "sha256:9edba65473324c2ea9684b1f944fe3191db3345e50b6d04571d10ed164f8d7bd"},
+    {file = "identify-2.6.3.tar.gz", hash = "sha256:62f5dae9b5fef52c84cc188514e9ea4f3f636b1d8799ab5ebc475471f9e47a02"},
 ]
 
 [package.extras]
@@ -984,29 +984,6 @@ files = [
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 ]
 
-[[package]]
-name = "importlib-metadata"
-version = "8.5.0"
-description = "Read metadata from Python packages"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.dependencies]
-zipp = ">=3.20"
-
-[package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
-cover = ["pytest-cov"]
-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
-perf = ["ipython"]
-test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
-type = ["pytest-mypy"]
-
 [[package]]
 name = "importlib-resources"
 version = "6.4.5"
@@ -1018,9 +995,6 @@ files = [
     {file = "importlib_resources-6.4.5.tar.gz", hash = "sha256:980862a1d16c9e147a59603677fa2aa5fd82b87f223b6cb870695bcfce830065"},
 ]
 
-[package.dependencies]
-zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
-
 [package.extras]
 check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
 cover = ["pytest-cov"]
@@ -1408,7 +1382,6 @@ files = [
 contourpy = ">=1.0.1"
 cycler = ">=0.10"
 fonttools = ">=4.22.0"
-importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
 kiwisolver = ">=1.3.1"
 numpy = ">=1.23"
 packaging = ">=20.0"
@@ -1632,9 +1605,6 @@ files = [
     {file = "multidict-6.1.0.tar.gz", hash = "sha256:22ae2ebf9b0c69d206c003e2f6a914ea33f0a932d4aa16f236afc049d9958f4a"},
 ]
 
-[package.dependencies]
-typing-extensions = {version = ">=4.1.0", markers = "python_version < \"3.11\""}
-
 [[package]]
 name = "mypy-extensions"
 version = "1.0.0"
@@ -1648,20 +1618,21 @@ files = [
 
 [[package]]
 name = "networkx"
-version = "3.2.1"
+version = "3.4.2"
 description = "Python package for creating and manipulating graphs and networks"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 files = [
-    {file = "networkx-3.2.1-py3-none-any.whl", hash = "sha256:f18c69adc97877c42332c170849c96cefa91881c99a7cb3e95b7c659ebdc1ec2"},
-    {file = "networkx-3.2.1.tar.gz", hash = "sha256:9f1bb5cf3409bf324e0a722c20bdb4c20ee39bf1c30ce8ae499c8502b0b5e0c6"},
+    {file = "networkx-3.4.2-py3-none-any.whl", hash = "sha256:df5d4365b724cf81b8c6a7312509d0c22386097011ad1abe274afd5e9d3bbc5f"},
+    {file = "networkx-3.4.2.tar.gz", hash = "sha256:307c3669428c5362aab27c8a1260aa8f47c4e91d3891f48be0141738d8d053e1"},
 ]
 
 [package.extras]
-default = ["matplotlib (>=3.5)", "numpy (>=1.22)", "pandas (>=1.4)", "scipy (>=1.9,!=1.11.0,!=1.11.1)"]
-developer = ["changelist (==0.4)", "mypy (>=1.1)", "pre-commit (>=3.2)", "rtoml"]
-doc = ["nb2plots (>=0.7)", "nbconvert (<7.9)", "numpydoc (>=1.6)", "pillow (>=9.4)", "pydata-sphinx-theme (>=0.14)", "sphinx (>=7)", "sphinx-gallery (>=0.14)", "texext (>=0.6.7)"]
-extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.11)", "sympy (>=1.10)"]
+default = ["matplotlib (>=3.7)", "numpy (>=1.24)", "pandas (>=2.0)", "scipy (>=1.10,!=1.11.0,!=1.11.1)"]
+developer = ["changelist (==0.5)", "mypy (>=1.1)", "pre-commit (>=3.2)", "rtoml"]
+doc = ["intersphinx-registry", "myst-nb (>=1.1)", "numpydoc (>=1.8.0)", "pillow (>=9.4)", "pydata-sphinx-theme (>=0.15)", "sphinx (>=7.3)", "sphinx-gallery (>=0.16)", "texext (>=0.6.7)"]
+example = ["cairocffi (>=1.7)", "contextily (>=1.6)", "igraph (>=0.11)", "momepy (>=0.7.2)", "osmnx (>=1.9)", "scikit-learn (>=1.5)", "seaborn (>=0.13)"]
+extra = ["lxml (>=4.6)", "pydot (>=3.0.1)", "pygraphviz (>=1.14)", "sympy (>=1.10)"]
 test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
 
 [[package]]
@@ -1690,7 +1661,6 @@ files = [
 argcomplete = ">=1.9.4,<4"
 colorlog = ">=2.6.1,<7"
 packaging = ">=20.9"
-tomli = {version = ">=1", markers = "python_version < \"3.11\""}
 virtualenv = ">=20.14.1"
 
 [package.extras]
@@ -1966,7 +1936,6 @@ files = [
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
     {version = ">=1.23.2", markers = "python_version == \"3.11\""},
     {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
@@ -2262,7 +2231,6 @@ files = [
 
 [package.dependencies]
 "ruamel.yaml" = ">=0.15"
-tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "propcache"
@@ -2474,53 +2442,53 @@ test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
 
 [[package]]
 name = "pyarrow"
-version = "18.0.0"
+version = "18.1.0"
 description = "Python library for Apache Arrow"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "pyarrow-18.0.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:2333f93260674e185cfbf208d2da3007132572e56871f451ba1a556b45dae6e2"},
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 [package.extras]
@@ -2595,25 +2563,23 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
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+version = "7.4.4"
 description = "pytest: simple powerful testing with Python"
 optional = false
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 iniconfig = "*"
 packaging = "*"
-pluggy = ">=1.5,<2"
-tomli = {version = ">=1", markers = "python_version < \"3.11\""}
+pluggy = ">=0.12,<2.0"
 
 [package.extras]
-dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "python-dateutil"
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 pygments = ">=2.13.0,<3.0.0"
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 [package.extras]
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 [package.extras]
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 [[package]]
 name = "seaborn"
@@ -3213,38 +3181,36 @@ files = [
 
 [[package]]
 name = "sphinx"
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+version = "8.1.3"
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 [[package]]
@@ -3271,22 +3237,22 @@ test = ["httpx", "pytest (>=6)"]
 
 [[package]]
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 [package.dependencies]
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+sphinx = ">=8.0.2"
 
 [package.extras]
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+docs = ["furo (>=2024.8.6)"]
 numpy = ["nptyping (>=2.5)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.4.4)", "defusedxml (>=0.7.1)", "diff-cover (>=9)", "pytest (>=8.1.1)", "pytest-cov (>=5)", "sphobjinv (>=2.3.1)", "typing-extensions (>=4.11)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "defusedxml (>=0.7.1)", "diff-cover (>=9.1.1)", "pytest (>=8.3.2)", "pytest-cov (>=5)", "sphobjinv (>=2.3.1.1)", "typing-extensions (>=4.12.2)"]
 
 [[package]]
 name = "sphinx-click"
@@ -3444,7 +3410,6 @@ files = [
 
 [package.dependencies]
 anyio = ">=3.4.0,<5"
-typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
 full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7)", "pyyaml"]
@@ -3599,14 +3564,14 @@ files = [
 ]
 
 [[package]]
-name = "tomli"
-version = "2.1.0"
-description = "A lil' TOML parser"
-optional = false
-python-versions = ">=3.8"
+name = "toml"
+version = "0.10.2"
+description = "Python Library for Tom's Obvious, Minimal Language"
+optional = true
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
-    {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"},
-    {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"},
+    {file = "toml-0.10.2-py2.py3-none-any.whl", hash = "sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b"},
+    {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
 ]
 
 [[package]]
@@ -3730,22 +3695,42 @@ text = ["ipadic (>=1.0.0)", "mecab-python3 (>=1.0.6)", "nltk (>3.8.1)", "regex (
 typing = ["mypy (==1.13.0)", "torch (==2.5.1)", "types-PyYAML", "types-emoji", "types-protobuf", "types-requests", "types-setuptools", "types-six", "types-tabulate"]
 visual = ["SciencePlots (>=2.0.0)", "matplotlib (>=3.6.0)"]
 
+[[package]]
+name = "tornado"
+version = "6.4.2"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+optional = true
+python-versions = ">=3.8"
+files = [
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+    {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:072ce12ada169c5b00b7d92a99ba089447ccc993ea2143c9ede887e0937aa803"},
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+    {file = "tornado-6.4.2-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:932d195ca9015956fa502c6b56af9eb06106140d844a335590c1ec7f5277d10c"},
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+    {file = "tornado-6.4.2-cp38-abi3-win_amd64.whl", hash = "sha256:908b71bf3ff37d81073356a5fadcc660eb10c1476ee6e2725588626ce7e5ca38"},
+    {file = "tornado-6.4.2.tar.gz", hash = "sha256:92bad5b4746e9879fd7bf1eb21dce4e3fc5128d71601f80005afa39237ad620b"},
+]
+
 [[package]]
 name = "tqdm"
-version = "4.67.0"
+version = "4.67.1"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.67.0-py3-none-any.whl", hash = "sha256:0cd8af9d56911acab92182e88d763100d4788bdf421d251616040cc4d44863be"},
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+    {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"},
+    {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [package.extras]
-dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"]
 discord = ["requests"]
 notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
@@ -3773,31 +3758,6 @@ build = ["cmake (>=3.20)", "lit"]
 tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
 tutorials = ["matplotlib", "pandas", "tabulate"]
 
-[[package]]
-name = "types-pyyaml"
-version = "6.0.12.20240917"
-description = "Typing stubs for PyYAML"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[[package]]
-name = "types-requests"
-version = "2.32.0.20241016"
-description = "Typing stubs for requests"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.dependencies]
-urllib3 = ">=2"
-
 [[package]]
 name = "typing-extensions"
 version = "4.12.2"
@@ -3851,20 +3811,19 @@ files = [
 [package.dependencies]
 click = ">=7.0"
 h11 = ">=0.8"
-typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 standard = ["colorama (>=0.4)", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.27.1"
+version = "20.28.0"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "virtualenv-20.27.1-py3-none-any.whl", hash = "sha256:f11f1b8a29525562925f745563bfd48b189450f61fb34c4f9cc79dd5aa32a1f4"},
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+    {file = "virtualenv-20.28.0-py3-none-any.whl", hash = "sha256:23eae1b4516ecd610481eda647f3a7c09aea295055337331bb4e6892ecce47b0"},
+    {file = "virtualenv-20.28.0.tar.gz", hash = "sha256:2c9c3262bb8e7b87ea801d715fae4495e6032450c71d2309be9550e7364049aa"},
 ]
 
 [package.dependencies]
@@ -3878,94 +3837,82 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess
 
 [[package]]
 name = "watchfiles"
-version = "0.24.0"
+version = "1.0.0"
 description = "Simple, modern and high performance file watching and code reload in python."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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 [package.dependencies]
@@ -4051,117 +3998,129 @@ files = [
 
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+version = "2024.11.0"
 description = "N-D labeled arrays and datasets in Python"
 optional = false
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-packaging = ">=23.1"
-pandas = ">=2.0"
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+packaging = ">=23.2"
+pandas = ">=2.1"
 
 [package.extras]
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-complete = ["xarray[accel,dev,io,parallel,viz]"]
-dev = ["hypothesis", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "xarray[complete]"]
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 parallel = ["dask[complete]"]
-viz = ["matplotlib", "nc-time-axis", "seaborn"]
+viz = ["cartopy", "matplotlib", "nc-time-axis", "seaborn"]
+
+[[package]]
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+description = "Source of XYZ tiles providers"
+optional = true
+python-versions = ">=3.8"
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+    {file = "yarl-1.18.0-cp39-cp39-win_amd64.whl", hash = "sha256:2d90f2e4d16a5b0915ee065218b435d2ef619dd228973b1b47d262a6f7cd8fa5"},
+    {file = "yarl-1.18.0-py3-none-any.whl", hash = "sha256:dbf53db46f7cf176ee01d8d98c39381440776fcda13779d269a8ba664f69bec0"},
+    {file = "yarl-1.18.0.tar.gz", hash = "sha256:20d95535e7d833889982bfe7cc321b7f63bf8879788fee982c76ae2b24cfb715"},
 ]
 
 [package.dependencies]
@@ -4169,26 +4128,10 @@ idna = ">=2.0"
 multidict = ">=4.0"
 propcache = ">=0.2.0"
 
-[[package]]
-name = "zipp"
-version = "3.21.0"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"},
-    {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"},
-]
-
-[package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
-cover = ["pytest-cov"]
-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
-test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
-type = ["pytest-mypy"]
+[extras]
+fit = ["curve-curator", "toml"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.9,<=3.13"
-content-hash = "9b76fe3f4aaf979f00ea371363124781c106ce3da04241a5c4309cbfbc0a07e7"
+python-versions = ">=3.11,<3.13"
+content-hash = "674c80d1f91d8a55d7d3f81712f8b68cc42808cc4936040140c4cc031f55ae7d"
diff --git a/pyproject.toml b/pyproject.toml
index c9a21da..c428a8e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,7 +7,7 @@ license = "GPL-3.0"
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = ">=3.9,<=3.13"
+python = ">=3.11,<3.13"
 numpy = ">=1.20,<2.0"
 scipy = "*"
 scikit-learn = ">=1.4,<1.6"
@@ -24,7 +24,11 @@ ray = {extras = ["tune"], version = "^2.37.0"}
 plotly = "*"
 matplotlib = "*"
 importlib-resources = "*"
+curve-curator = {version = "*", optional = true}
+toml = {version = "^0.10.2", optional = true}
 
+[tool.poetry.extras]
+fit = ["curve-curator", "toml"]
 
 [tool.poetry.group.development.dependencies]
 sphinx-autodoc-typehints = "<3.0"
@@ -47,8 +51,6 @@ pre-commit = "*"
 pre-commit-hooks = "*"
 pyupgrade = "*"
 pep8-naming = "*"
-types-requests = "*"
-types-PyYAML = "*"
 
 [tool.black]
 line-length = 120
diff --git a/requirements.txt b/requirements.txt
index e7afaf4..6606cf0 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,86 +1,159 @@
-aiohappyeyeballs==2.4.3 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-aiohttp==3.11.4 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-aiosignal==1.3.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-async-timeout==5.0.1 ; python_version >= "3.9" and python_version < "3.11"
-attrs==24.2.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-certifi==2024.8.30 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-charset-normalizer==3.4.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-click==8.1.7 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-colorama==0.4.6 ; python_version >= "3.9" and python_full_version <= "3.13.0" and platform_system == "Windows"
-contourpy==1.3.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-cycler==0.12.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-filelock==3.16.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-flaky==3.8.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-fonttools==4.55.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-frozenlist==1.5.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-fsspec==2024.10.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-fsspec[http]==2024.10.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-idna==3.10 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-importlib-resources==6.4.5 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-jinja2==3.1.4 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-joblib==1.4.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-jsonschema-specifications==2024.10.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-jsonschema==4.23.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-kiwisolver==1.4.7 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-lightning-utilities==0.11.8 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-markupsafe==3.0.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-matplotlib==3.9.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-mpmath==1.3.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-msgpack==1.1.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-multidict==6.1.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-networkx==3.2.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-numpy==1.26.4 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cublas-cu12==12.1.3.1 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cuda-cupti-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cuda-nvrtc-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cuda-runtime-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cudnn-cu12==9.1.0.70 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cufft-cu12==11.0.2.54 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-curand-cu12==10.3.2.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cusolver-cu12==11.4.5.107 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-cusparse-cu12==12.1.0.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-nccl-cu12==2.20.5 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-nvjitlink-cu12==12.6.77 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-nvidia-nvtx-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-packaging==24.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pandas-flavor==0.6.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pandas==2.2.3 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-patsy==1.0.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pillow==11.0.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pingouin==0.5.5 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-plotly==5.24.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-propcache==0.2.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-protobuf==5.28.3 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-psutil==6.1.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pyarrow==18.0.0 ; sys_platform != "darwin" and python_version >= "3.9" and python_full_version <= "3.13.0" or platform_machine != "x86_64" and python_version >= "3.9" and python_full_version <= "3.13.0"
-pyparsing==3.2.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-python-dateutil==2.9.0.post0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pytorch-lightning==2.4.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pytz==2024.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-pyyaml==6.0.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-ray[tune]==2.39.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-referencing==0.35.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-requests==2.32.3 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-rpds-py==0.21.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-scikit-learn==1.5.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-scipy==1.13.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-seaborn==0.13.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-setuptools==75.5.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-six==1.16.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-statsmodels==0.14.4 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-sympy==1.13.3 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-tabulate==0.9.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-tenacity==9.0.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-tensorboardx==2.6.2.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-threadpoolctl==3.5.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-torch-geometric==2.6.1 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-torch==2.4.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-torchmetrics==1.6.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-tqdm==4.67.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-triton==3.0.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version < "3.13" and python_version >= "3.9"
-typing-extensions==4.12.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-tzdata==2024.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-urllib3==2.2.3 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-xarray==2024.7.0 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-yarl==1.17.2 ; python_version >= "3.9" and python_full_version <= "3.13.0"
-zipp==3.21.0 ; python_version >= "3.9" and python_version < "3.10"
+aiohappyeyeballs==2.4.3 ; python_version >= "3.11" and python_version < "3.13"
+aiohttp==3.11.7 ; python_version >= "3.11" and python_version < "3.13"
+aiosignal==1.3.1 ; python_version >= "3.11" and python_version < "3.13"
+alabaster==1.0.0 ; python_version >= "3.11" and python_version < "3.13"
+anyio==4.6.2.post1 ; python_version >= "3.11" and python_version < "3.13"
+argcomplete==3.5.1 ; python_version >= "3.11" and python_version < "3.13"
+attrs==24.2.0 ; python_version >= "3.11" and python_version < "3.13"
+babel==2.16.0 ; python_version >= "3.11" and python_version < "3.13"
+bandit==1.7.10 ; python_version >= "3.11" and python_version < "3.13"
+black==24.10.0 ; python_version >= "3.11" and python_version < "3.13"
+bokeh==3.4.3 ; python_version >= "3.11" and python_version < "3.13"
+certifi==2024.8.30 ; python_version >= "3.11" and python_version < "3.13"
+cfgv==3.4.0 ; python_version >= "3.11" and python_version < "3.13"
+charset-normalizer==3.4.0 ; python_version >= "3.11" and python_version < "3.13"
+click==8.1.7 ; python_version >= "3.11" and python_version < "3.13"
+colorama==0.4.6 ; python_version >= "3.11" and python_version < "3.13"
+colorlog==6.9.0 ; python_version >= "3.11" and python_version < "3.13"
+contourpy==1.3.1 ; python_version >= "3.11" and python_version < "3.13"
+curve-curator==0.5.1 ; python_version >= "3.11" and python_version < "3.13"
+cycler==0.12.1 ; python_version >= "3.11" and python_version < "3.13"
+darglint==1.8.1 ; python_version >= "3.11" and python_version < "3.13"
+distlib==0.3.9 ; python_version >= "3.11" and python_version < "3.13"
+docutils==0.21.2 ; python_version >= "3.11" and python_version < "3.13"
+filelock==3.16.1 ; python_version >= "3.11" and python_version < "3.13"
+flake8-bandit==4.1.1 ; python_version >= "3.11" and python_version < "3.13"
+flake8-bugbear==24.10.31 ; python_version >= "3.11" and python_version < "3.13"
+flake8-docstrings==1.7.0 ; python_version >= "3.11" and python_version < "3.13"
+flake8-rst-docstrings==0.3.0 ; python_version >= "3.11" and python_version < "3.13"
+flake8==7.1.1 ; python_version >= "3.11" and python_version < "3.13"
+flaky==3.8.1 ; python_version >= "3.11" and python_version < "3.13"
+fonttools==4.55.0 ; python_version >= "3.11" and python_version < "3.13"
+frozenlist==1.5.0 ; python_version >= "3.11" and python_version < "3.13"
+fsspec==2024.10.0 ; python_version >= "3.11" and python_version < "3.13"
+fsspec[http]==2024.10.0 ; python_version >= "3.11" and python_version < "3.13"
+h11==0.14.0 ; python_version >= "3.11" and python_version < "3.13"
+identify==2.6.3 ; python_version >= "3.11" and python_version < "3.13"
+idna==3.10 ; python_version >= "3.11" and python_version < "3.13"
+imagesize==1.4.1 ; python_version >= "3.11" and python_version < "3.13"
+importlib-resources==6.4.5 ; python_version >= "3.11" and python_version < "3.13"
+iniconfig==2.0.0 ; python_version >= "3.11" and python_version < "3.13"
+isort==5.13.2 ; python_version >= "3.11" and python_version < "3.13"
+jinja2==3.1.4 ; python_version >= "3.11" and python_version < "3.13"
+joblib==1.4.2 ; python_version >= "3.11" and python_version < "3.13"
+jsonschema-specifications==2024.10.1 ; python_version >= "3.11" and python_version < "3.13"
+jsonschema==4.23.0 ; python_version >= "3.11" and python_version < "3.13"
+kiwisolver==1.4.7 ; python_version >= "3.11" and python_version < "3.13"
+lightning-utilities==0.11.9 ; python_version >= "3.11" and python_version < "3.13"
+markdown-it-py==3.0.0 ; python_version >= "3.11" and python_version < "3.13"
+markupsafe==3.0.2 ; python_version >= "3.11" and python_version < "3.13"
+matplotlib==3.9.2 ; python_version >= "3.11" and python_version < "3.13"
+mccabe==0.7.0 ; python_version >= "3.11" and python_version < "3.13"
+mdurl==0.1.2 ; python_version >= "3.11" and python_version < "3.13"
+mpmath==1.3.0 ; python_version >= "3.11" and python_version < "3.13"
+msgpack==1.1.0 ; python_version >= "3.11" and python_version < "3.13"
+multidict==6.1.0 ; python_version >= "3.11" and python_version < "3.13"
+mypy-extensions==1.0.0 ; python_version >= "3.11" and python_version < "3.13"
+networkx==3.4.2 ; python_version >= "3.11" and python_version < "3.13"
+nodeenv==1.9.1 ; python_version >= "3.11" and python_version < "3.13"
+nox-poetry==1.0.3 ; python_version >= "3.11" and python_version < "3.13"
+nox==2024.10.9 ; python_version >= "3.11" and python_version < "3.13"
+numpy==1.26.4 ; python_version >= "3.11" and python_version < "3.13"
+nvidia-cublas-cu12==12.1.3.1 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-cuda-cupti-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-cuda-nvrtc-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-cuda-runtime-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-cudnn-cu12==9.1.0.70 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-cufft-cu12==11.0.2.54 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-curand-cu12==10.3.2.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-cusolver-cu12==11.4.5.107 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-cusparse-cu12==12.1.0.106 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-nccl-cu12==2.20.5 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-nvjitlink-cu12==12.6.85 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+nvidia-nvtx-cu12==12.1.105 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version >= "3.11" and python_version < "3.13"
+packaging==24.2 ; python_version >= "3.11" and python_version < "3.13"
+pandas-flavor==0.6.0 ; python_version >= "3.11" and python_version < "3.13"
+pandas==2.2.3 ; python_version >= "3.11" and python_version < "3.13"
+pathspec==0.12.1 ; python_version >= "3.11" and python_version < "3.13"
+patsy==1.0.1 ; python_version >= "3.11" and python_version < "3.13"
+pbr==6.1.0 ; python_version >= "3.11" and python_version < "3.13"
+pep8-naming==0.14.1 ; python_version >= "3.11" and python_version < "3.13"
+pillow==11.0.0 ; python_version >= "3.11" and python_version < "3.13"
+pingouin==0.5.5 ; python_version >= "3.11" and python_version < "3.13"
+platformdirs==4.3.6 ; python_version >= "3.11" and python_version < "3.13"
+plotly==5.24.1 ; python_version >= "3.11" and python_version < "3.13"
+pluggy==1.5.0 ; python_version >= "3.11" and python_version < "3.13"
+pre-commit-hooks==5.0.0 ; python_version >= "3.11" and python_version < "3.13"
+pre-commit==4.0.1 ; python_version >= "3.11" and python_version < "3.13"
+propcache==0.2.0 ; python_version >= "3.11" and python_version < "3.13"
+protobuf==5.28.3 ; python_version >= "3.11" and python_version < "3.13"
+psutil==6.1.0 ; python_version >= "3.11" and python_version < "3.13"
+pyarrow==18.1.0 ; sys_platform != "darwin" and python_version >= "3.11" and python_version < "3.13" or platform_machine != "x86_64" and python_version >= "3.11" and python_version < "3.13"
+pycodestyle==2.12.1 ; python_version >= "3.11" and python_version < "3.13"
+pydocstyle==6.3.0 ; python_version >= "3.11" and python_version < "3.13"
+pyflakes==3.2.0 ; python_version >= "3.11" and python_version < "3.13"
+pygments==2.18.0 ; python_version >= "3.11" and python_version < "3.13"
+pyparsing==3.2.0 ; python_version >= "3.11" and python_version < "3.13"
+pytest==7.4.4 ; python_version >= "3.11" and python_version < "3.13"
+python-dateutil==2.9.0.post0 ; python_version >= "3.11" and python_version < "3.13"
+pytorch-lightning==2.4.0 ; python_version >= "3.11" and python_version < "3.13"
+pytz==2024.2 ; python_version >= "3.11" and python_version < "3.13"
+pyupgrade==3.19.0 ; python_version >= "3.11" and python_version < "3.13"
+pyyaml==6.0.2 ; python_version >= "3.11" and python_version < "3.13"
+ray[tune]==2.39.0 ; python_version >= "3.11" and python_version < "3.13"
+referencing==0.35.1 ; python_version >= "3.11" and python_version < "3.13"
+requests==2.32.3 ; python_version >= "3.11" and python_version < "3.13"
+restructuredtext-lint==1.4.0 ; python_version >= "3.11" and python_version < "3.13"
+rich==13.9.4 ; python_version >= "3.11" and python_version < "3.13"
+rpds-py==0.21.0 ; python_version >= "3.11" and python_version < "3.13"
+ruamel-yaml-clib==0.2.12 ; platform_python_implementation == "CPython" and python_version < "3.13" and python_version >= "3.11"
+ruamel-yaml==0.18.6 ; python_version >= "3.11" and python_version < "3.13"
+scikit-learn==1.5.2 ; python_version >= "3.11" and python_version < "3.13"
+scipy==1.14.1 ; python_version >= "3.11" and python_version < "3.13"
+seaborn==0.13.2 ; python_version >= "3.11" and python_version < "3.13"
+setuptools==75.6.0 ; python_version >= "3.11" and python_version < "3.13"
+six==1.16.0 ; python_version >= "3.11" and python_version < "3.13"
+sniffio==1.3.1 ; python_version >= "3.11" and python_version < "3.13"
+snowballstemmer==2.2.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinx-autobuild==2024.10.3 ; python_version >= "3.11" and python_version < "3.13"
+sphinx-autodoc-typehints==2.5.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinx-click==6.0.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinx-rtd-theme==3.0.2 ; python_version >= "3.11" and python_version < "3.13"
+sphinx==8.1.3 ; python_version >= "3.11" and python_version < "3.13"
+sphinxcontrib-applehelp==2.0.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinxcontrib-devhelp==2.0.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinxcontrib-htmlhelp==2.1.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinxcontrib-jquery==4.1 ; python_version >= "3.11" and python_version < "3.13"
+sphinxcontrib-jsmath==1.0.1 ; python_version >= "3.11" and python_version < "3.13"
+sphinxcontrib-qthelp==2.0.0 ; python_version >= "3.11" and python_version < "3.13"
+sphinxcontrib-serializinghtml==2.0.0 ; python_version >= "3.11" and python_version < "3.13"
+starlette==0.41.3 ; python_version >= "3.11" and python_version < "3.13"
+statsmodels==0.14.4 ; python_version >= "3.11" and python_version < "3.13"
+stevedore==5.4.0 ; python_version >= "3.11" and python_version < "3.13"
+sympy==1.13.3 ; python_version >= "3.11" and python_version < "3.13"
+tabulate==0.9.0 ; python_version >= "3.11" and python_version < "3.13"
+tenacity==9.0.0 ; python_version >= "3.11" and python_version < "3.13"
+tensorboardx==2.6.2.2 ; python_version >= "3.11" and python_version < "3.13"
+threadpoolctl==3.5.0 ; python_version >= "3.11" and python_version < "3.13"
+tokenize-rt==6.1.0 ; python_version >= "3.11" and python_version < "3.13"
+toml==0.10.2 ; python_version >= "3.11" and python_version < "3.13"
+tomlkit==0.13.2 ; python_version >= "3.11" and python_version < "3.13"
+torch-geometric==2.6.1 ; python_version >= "3.11" and python_version < "3.13"
+torch==2.4.0 ; python_version >= "3.11" and python_version < "3.13"
+torchmetrics==1.6.0 ; python_version >= "3.11" and python_version < "3.13"
+tornado==6.4.2 ; python_version >= "3.11" and python_version < "3.13"
+tqdm==4.67.1 ; python_version >= "3.11" and python_version < "3.13"
+triton==3.0.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version < "3.13" and python_version >= "3.11"
+types-pyyaml==6.0.12.20240917 ; python_version >= "3.11" and python_version < "3.13"
+types-requests==2.32.0.20241016 ; python_version >= "3.11" and python_version < "3.13"
+types-toml==0.10.8.20240310 ; python_version >= "3.11" and python_version < "3.13"
+typing-extensions==4.12.2 ; python_version >= "3.11" and python_version < "3.13"
+tzdata==2024.2 ; python_version >= "3.11" and python_version < "3.13"
+urllib3==2.2.3 ; python_version >= "3.11" and python_version < "3.13"
+uvicorn==0.32.1 ; python_version >= "3.11" and python_version < "3.13"
+virtualenv==20.28.0 ; python_version >= "3.11" and python_version < "3.13"
+watchfiles==1.0.0 ; python_version >= "3.11" and python_version < "3.13"
+websockets==14.1 ; python_version >= "3.11" and python_version < "3.13"
+xarray==2024.11.0 ; python_version >= "3.11" and python_version < "3.13"
+xyzservices==2024.9.0 ; python_version >= "3.11" and python_version < "3.13"
+yarl==1.18.0 ; python_version >= "3.11" and python_version < "3.13"
diff --git a/setup.cfg b/setup.cfg
index 93ebefd..6ab92a9 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -14,5 +14,5 @@ max-complexity = 10
 docstring-convention = google
 per-file-ignores =
 	tests/*:S101,S301,S403
-	drevalpy/datasets/toy.py:S403,S301
+	drevalpy/datasets/curvecurator.py:S404,S603
 docstring_style = sphinx
diff --git a/tests/CTRPv2_sample_test/CTRPv2_sample_test_raw.csv b/tests/CTRPv2_sample_test/CTRPv2_sample_test_raw.csv
new file mode 100644
index 0000000..8af4b0a
--- /dev/null
+++ b/tests/CTRPv2_sample_test/CTRPv2_sample_test_raw.csv
@@ -0,0 +1,113 @@
+,dose,response,sample,drug,replicate
+8390,0.002,1.0955079850281488,2004,afatinib,1
+8391,0.002,0.9369539186580808,2004,afatinib,2
+8392,0.0041,0.8294920158973823,2004,afatinib,1
+8393,0.0041,0.9105435966967405,2004,afatinib,2
+8394,0.0081,1.0098562889944274,2004,afatinib,1
+8395,0.0081,1.0455847467457329,2004,afatinib,2
+8396,0.016,0.7997383630343657,2004,afatinib,1
+8397,0.016,0.8839888023747461,2004,afatinib,2
+8398,0.032,0.8273100425752845,2004,afatinib,1
+8399,0.032,0.8408964152537145,2004,afatinib,2
+8400,0.065,0.8947769516844151,2004,afatinib,1
+8401,0.065,1.042899400329442,2004,afatinib,2
+8402,0.13,1.0853798270461994,2004,afatinib,1
+8403,0.13,0.917576278566009,2004,afatinib,2
+8404,0.26,0.672870137616213,2004,afatinib,1
+8405,0.26,0.5671884265995343,2004,afatinib,2
+8406,0.52,0.7038305298908818,2004,afatinib,1
+8407,0.52,0.7630238195861496,2004,afatinib,2
+8408,1.0,0.7775460358825583,2004,afatinib,1
+8409,1.0,0.7411821282906099,2004,afatinib,2
+8410,2.1,0.7033915944835474,2004,afatinib,1
+8411,2.1,0.6444766524849002,2004,afatinib,2
+8412,4.2,0.5389786383267785,2004,afatinib,1
+8413,4.2,0.4623316390568497,2004,afatinib,2
+8414,8.3,0.1767766952966369,2004,afatinib,1
+8415,8.3,0.25366563664522,2004,afatinib,2
+8416,17.0,0.0616822841178651,2004,afatinib,1
+8417,17.0,0.0207175900046665,2004,afatinib,2
+8418,33.0,0.0303954671066339,2004,afatinib,1
+8419,33.0,0.0209486342434427,2004,afatinib,2
+8420,66.0,0.0114302439117525,2004,afatinib,1
+8421,66.0,0.0172411521881556,2004,afatinib,2
+10938,0.002,1.0731858962374974,2004,lapatinib,1
+10939,0.002,1.1915999762950489,2004,lapatinib,2
+10940,0.0041,0.9126920057518458,2004,lapatinib,1
+10941,0.0041,1.007025349315796,2004,lapatinib,2
+10942,0.0081,0.7846928718872889,2004,lapatinib,1
+10943,0.0081,1.146232732176102,2004,lapatinib,2
+10944,0.016,1.0700809956566426,2004,lapatinib,1
+10945,0.016,1.163603870176683,2004,lapatinib,2
+10946,0.032,0.9392037019011334,2004,lapatinib,1
+10947,0.032,1.061003929954875,2004,lapatinib,2
+10948,0.065,0.9427714662399728,2004,lapatinib,1
+10949,0.065,0.925240293045082,2004,lapatinib,2
+10950,0.13,0.8787349618012162,2004,lapatinib,1
+10951,0.13,1.0684356354627889,2004,lapatinib,2
+10952,0.26,1.1941631870745897,2004,lapatinib,1
+10953,0.26,1.1120333073823458,2004,lapatinib,2
+10954,0.52,0.8703695562159134,2004,lapatinib,1
+10955,0.52,1.4400311304072253,2004,lapatinib,2
+10956,1.0,1.0551733260722722,2004,lapatinib,1
+10957,1.0,1.0025227668357692,2004,lapatinib,2
+10958,2.1,1.2177348208537884,2004,lapatinib,1
+10959,2.1,1.0322339596514074,2004,lapatinib,2
+10960,4.2,0.8959561310220235,2004,lapatinib,1
+10961,4.2,1.1028984805171396,2004,lapatinib,2
+10962,8.3,0.6167680767672187,2004,lapatinib,1
+10963,8.3,0.5458589076649897,2004,lapatinib,2
+10964,17.0,0.2506941089752694,2004,lapatinib,1
+10965,17.0,0.2895732015486608,2004,lapatinib,2
+10966,33.0,0.02948244534048,2004,lapatinib,1
+10967,33.0,0.0204607097356807,2004,lapatinib,2
+10968,66.0,0.8762412270452258,2004,lapatinib,1
+10969,66.0,0.8129282899636412,2004,lapatinib,2
+12457260,0.002,1.025928365774697,LC1F,afatinib,1
+12457261,0.002,0.6766585868878507,LC1F,afatinib,2
+12457262,0.0041,1.444529833683516,LC1F,afatinib,1
+12457263,0.0041,0.5180272874509741,LC1F,afatinib,2
+12457264,0.0081,0.4746710604752596,LC1F,afatinib,1
+12457265,0.0081,1.1920956518590946,LC1F,afatinib,2
+12457266,0.016,0.875330654293931,LC1F,afatinib,1
+12457267,0.016,0.8643574745348869,LC1F,afatinib,2
+12457268,0.032,0.5833363976667916,LC1F,afatinib,1
+12457269,0.032,0.3755299817352323,LC1F,afatinib,2
+12457270,0.065,0.5921358059268162,LC1F,afatinib,1
+12457271,0.065,0.3942000870281391,LC1F,afatinib,2
+12457272,0.13,0.972668431366438,LC1F,afatinib,1
+12457273,0.13,0.3570009949212661,LC1F,afatinib,2
+12457274,0.26,0.222518933313124,LC1F,afatinib,1
+12457275,0.26,0.4652248288515076,LC1F,afatinib,2
+12457276,0.52,0.4733568156183569,LC1F,afatinib,1
+12457277,0.52,0.7747485205636878,LC1F,afatinib,2
+12457278,1.0,0.874299815700005,LC1F,afatinib,1
+12457279,1.0,0.4989613594995253,LC1F,afatinib,2
+12457280,2.1,0.4266130490560336,LC1F,afatinib,1
+12457281,2.1,0.7323981235615232,LC1F,afatinib,2
+12457282,4.2,0.3612325994808814,LC1F,afatinib,1
+12457283,4.2,0.2242220399155036,LC1F,afatinib,2
+12457284,8.3,0.5695522088920328,LC1F,afatinib,1
+12457285,8.3,0.4490661864419671,LC1F,afatinib,2
+12457286,17.0,0.1640264068239951,LC1F,afatinib,1
+12457287,17.0,0.8542320898502386,LC1F,afatinib,2
+12457288,33.0,0.0726446317198823,LC1F,afatinib,1
+12457289,33.0,0.593286146203179,LC1F,afatinib,2
+12457290,66.0,0.0564454068844888,LC1F,afatinib,1
+12457291,66.0,0.0905588846596799,LC1F,afatinib,2
+12457569,0.002,0.6217471954827811,LC1F,lapatinib,1
+12457570,0.002,0.5792668457284896,LC1F,lapatinib,2
+12457571,0.0041,0.5893105503848409,LC1F,lapatinib,1
+12457572,0.0041,0.421031476804208,LC1F,lapatinib,2
+12457573,0.0081,0.7349917696370422,LC1F,lapatinib,1
+12457574,0.0081,0.6763303497309292,LC1F,lapatinib,2
+12457575,0.016,0.7469585019797846,LC1F,lapatinib,1
+12457576,0.016,0.4986156256760348,LC1F,lapatinib,2
+12457577,0.032,0.6383413456828999,LC1F,lapatinib,1
+12457578,0.032,0.5027105948821384,LC1F,lapatinib,2
+12457579,0.065,0.5600393097018835,LC1F,lapatinib,1
+12457580,0.065,0.3498964663987989,LC1F,lapatinib,2
+12457581,0.13,0.6767993087159954,LC1F,lapatinib,1
+12457582,0.13,0.3866231687276585,LC1F,lapatinib,2
+12457583,0.26,0.4310717725087979,LC1F,lapatinib,1
+12457584,0.26,0.3112185588455425,LC1F,lapatinib,2
diff --git a/tests/test_dataset.py b/tests/test_dataset.py
index 96eb38c..35ab3f5 100644
--- a/tests/test_dataset.py
+++ b/tests/test_dataset.py
@@ -1,7 +1,7 @@
 """Tests for the DrugResponseDataset and the FeatureDataset class."""
 
-import os
 import tempfile
+from pathlib import Path
 
 import networkx as nx
 import numpy as np
@@ -9,6 +9,7 @@
 from flaky import flaky
 
 from drevalpy.datasets.dataset import DrugResponseDataset, FeatureDataset
+from drevalpy.datasets.loader import load_dataset
 from drevalpy.utils import get_response_transformation
 
 # Tests for the DrugResponseDataset class
@@ -27,12 +28,13 @@ def test_response_dataset_load() -> None:
         drug_ids=data["drug_id"],
         response=data["response"],
     )
-    dataset.save("dataset.csv")
+    dataset_path = Path("dataset.csv")
+    dataset.save(dataset_path)
     del dataset
     # Load the dataset
-    dataset = DrugResponseDataset.from_csv("dataset.csv")
+    dataset = DrugResponseDataset.from_csv(dataset_path)
 
-    os.remove("dataset.csv")
+    dataset_path.unlink()
 
     # Check if the dataset loaded correctly
     assert np.array_equal(dataset.cell_line_ids, data["cell_line_id"])
@@ -40,6 +42,21 @@ def test_response_dataset_load() -> None:
     assert np.allclose(dataset.response, data["response"])
 
 
+def test_fitting_and_loading_custom_dataset():
+    """Test CurveCurator fitting of raw viability dataset and loading it."""
+    dataset_name = "CTRPv2_sample_test"
+    load_dataset(
+        dataset_name=dataset_name,
+        path_data=str(Path(__file__).parent),
+        measure="IC50",
+        curve_curator=True,
+        cores=200,
+    )
+    for f in (Path(__file__).parent / dataset_name).glob("*"):
+        if f.name != f"{dataset_name}_raw.csv":
+            f.unlink()
+
+
 def test_response_dataset_add_rows() -> None:
     """Test if the add_rows method works correctly."""
     dataset1 = DrugResponseDataset(
diff --git a/tests/test_run_suite.py b/tests/test_run_suite.py
index f309ced..7573e9c 100644
--- a/tests/test_run_suite.py
+++ b/tests/test_run_suite.py
@@ -24,6 +24,8 @@
             "n_trials_robustness": 2,
             "cross_study_datasets": ["GDSC1"],
             "curve_curator": False,
+            "curve_curator_cores": 1,
+            "measure": "LN_IC50",
             "overwrite": False,
             "optim_metric": "RMSE",
             "n_cv_splits": 2,