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../../experiments/mandema1992.py
from typing import Dict, List
from sbmlsim.data import DataSet, load_pkdb_dataframes_by_substance
from sbmlsim.fit import FitMapping, FitData
from sbmlsim.plot import Figure, Axis
from sbmlsim.simulation import Timecourse, TimecourseSim
from . import MidazolamSimulationExperiment
class Mandema1992(MidazolamSimulationExperiment):
def datasets(self) -> Dict[str, DataSet]:
dsets = {}
for fig_id in ["Fig1A", "Fig2A", "Fig3A"]:
dframes = load_pkdb_dataframes_by_substance(
f"{self.sid}_{fig_id}", data_path=self.data_path)
for substance, df in dframes.items():
dset = DataSet.from_df(df, self.ureg)
if substance == "midazolam":
dset.unit_conversion("mean", 1 / self.Mr.mid)
elif substance == "1-hydroxymidazolam":
dset.unit_conversion("mean", 1 / self.Mr.mid1oh)
else:
raise ValueError
dsets[f"{fig_id}_{substance}"] = dset
return dsets
def simulations(self) -> Dict[str, TimecourseSim]:
return {
**self.simulation_mid()
}
def simulation_mid(self) -> Dict[str, TimecourseSim]:
""" Mandema1992
- midazolam, iv, 0.1 [mg/kg] (infusion over 15 min)
- 1-hydroxy midazolam, iv, 0.15 [mg/kg] (infusion over 15 min)
- midazolam, po, 7.5 [mg]
"""
Q_ = self.Q_
bodyweight = Q_(69, 'kg') # avg. bodyweight of 8 individuals (sd=6kg)
# mid_iv = Q_(0.1, 'mg/kg') * bodyweight
mid_Ri = Q_(0.1, 'mg/kg') * bodyweight / Q_(15, 'min')
# if injected in 1 min use the IVDOSE_mid1oh parameter
# mid1oh_iv = Q_(0.15, 'mg/kg') * bodyweight
# but infused in 15 [min]
mid1oh_Ri = Q_(0.15, 'mg/kg') * bodyweight / Q_(15, 'min')
mid_po = Q_(7.5, 'mg')
tcsims = {}
tcsims["mid_iv"] = TimecourseSim([
Timecourse(start=0, end=15, steps=600, changes={
**self.default_changes(),
'Ri_mid': mid_Ri,
"BW": bodyweight
}),
Timecourse(start=0, end=300, steps=600, changes={
**self.default_changes(),
'Ri_mid': Q_(0, "mg_per_min"),
"BW": bodyweight
}),
])
tcsims["mid1oh_iv"] = TimecourseSim([
Timecourse(start=0, end=15, steps=100, changes={
**self.default_changes(),
# 'IVDOSE_mid1oh': mid1oh_iv
'Ri_mid1oh': mid1oh_Ri,
"BW": bodyweight
}),
Timecourse(start=0, end=300, steps=600, changes={
'Ri_mid1oh': Q_(0, 'mg_per_min'),
}),
])
tcsims["mid_po"] = TimecourseSim([
Timecourse(start=0, end=315, steps=700, changes={
**self.default_changes(),
'PODOSE_mid': mid_po,
"BW": bodyweight})
])
return tcsims
def fit_mappings(self) -> Dict[str, FitMapping]:
# fit mapping: which data maps on which simulation
fit_dict = {
"fm1": {"ref": "Fig1A_midazolam", "obs": "task_mid_iv", "yid": "[Cve_mid]"},
"fm2": {"ref": "Fig3A_midazolam", "obs": "task_mid_po", "yid": "[Cve_mid]"},
"fm3": {"ref": "Fig1A_1-hydroxymidazolam", "obs": "task_mid_iv", "yid": "[Cve_mid1oh]"},
"fm4": {"ref": "Fig2A_1-hydroxymidazolam", "obs": "task_mid1oh_iv", "yid": "[Cve_mid1oh]"},
"fm5": {"ref": "Fig3A_1-hydroxymidazolam", "obs": "task_mid_po", "yid": "[Cve_mid1oh]"},
}
mappings = {}
for key, values in fit_dict.items():
mappings[key] = FitMapping(
self,
reference=FitData(self, dataset=values["ref"], xid="time", yid="mean", yid_sd="mean_sd"),
observable=FitData(self, task=values["obs"], xid="time", yid=values["yid"])
)
return mappings
def figures(self) -> Dict[str, Figure]:
return {
**self.figure_mid(),
}
def figure_mid(self):
unit_time = "min"
unit_mid = "nmol/ml"
unit_mid1oh = "nmol/ml"
fig = Figure(self, sid="Fig1",
num_rows=2, num_cols=3, name=self.sid)
plots = fig.create_plots(
Axis("time", unit=unit_time),
legend=True
)
# simulation
plots[0].set_title("midazolam iv, 0.1 [mg/kg]")
plots[1].set_title("1-hydroxymidazolam iv, 0.15 [mg/kg]")
plots[2].set_title("midazolam po, 7.5 [mg]")
for k in (0, 1, 2):
plots[k].set_yaxis("midazolam", unit_mid)
plots[k].xaxis.label_visible = False
for k in (3, 4, 5):
plots[k].set_yaxis("1-hydroxymidazolam", unit_mid1oh)
plot_dict = {
"mid_iv": (plots[0], plots[3]),
"mid1oh_iv": (plots[1], plots[4]),
"mid_po": (plots[2], plots[5])
}
for key, plot in plot_dict.items():
# plot midazolam
p = plot[0]
p.add_data(task=f"task_{key}", xid="time", yid="[Cve_mid]",
label="mid (ve blood)", color="black")
#plot 1-hydroxymidazolam
p = plot[1]
p.add_data(task=f"task_{key}", xid="time", yid="[Cve_mid1oh]",
label="mid1oh (ve blood)", color="black")
# plot data
data_def = {
"Fig1A_midazolam": {'plot': plots[0], 'key': 'mid'},
"Fig1A_1-hydroxymidazolam": {'plot': plots[3], 'key': 'mid1oh'},
"Fig2A_1-hydroxymidazolam": {'plot': plots[4], 'key': 'mid1oh'},
"Fig3A_midazolam": {'plot': plots[2], 'key': 'mid'},
"Fig3A_1-hydroxymidazolam": {'plot': plots[5], 'key': 'mid1oh'},
}
for dset_key, dset_info in data_def.items():
p = dset_info['plot']
p.add_data(dataset=dset_key,
xid="time", yid="mean", yid_sd="mean_sd",
count=None, color="black", label=dset_info['key'])
return {"fig1": fig}