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class model.Model(clearance_rate=1, vol_c=1, dose=1)

A Pharmokinetic (PK) model. Defaults to Intravenous Bolus. Adding subcutaneous compartment changes model type

add_peripheral_compartment(pc_name=None, vol_p=1, q_p=1)

Adds peripheral compartment to model. Valid for both IVB and SC.

Parameters

• vol_p – int/float describing volume of per comp [ml]

• q_p – int/float describing drug quantiyin per comp [ng]

Returns

—

add_subcutaneous_compartment(absorption_rate=1)

Adds subcutaneous compartment to model with absorption rate specified.

Parameters

absorption_rate – int/float describing absorp. rate for SC [/h]

Returns

—

class solution.Solution(model)

Accepts a pharmacokinetic model and solves it, either returning a plot or arrays of the drug concentrations over time.

plot(name)

Plots the concentrations in the different compartments over time.

Parameters

name – the name of the model in question, e.g. IV, 2 peripheral compartments

Returns

—

solve(y0=None, t_eval=array([0.0, 0.001001, 0.002002, 0.003003, 0.004004, 0.00500501, 0.00600601, 0.00700701, 0.00800801, 0.00900901, 0.01001001, 0.01101101, 0.01201201, 0.01301301, 0.01401401, 0.01501502, 0.01601602, 0.01701702, 0.01801802, 0.01901902, 0.02002002, 0.02102102, 0.02202202, 0.02302302, 0.02402402, 0.02502503, 0.02602603, 0.02702703, 0.02802803, 0.02902903, 0.03003003, 0.03103103, 0.03203203, 0.03303303, 0.03403403, 0.03503504, 0.03603604, 0.03703704, 0.03803804, 0.03903904, 0.04004004, 0.04104104, 0.04204204, 0.04304304, 0.04404404, 0.04504505, 0.04604605, 0.04704705, 0.04804805, 0.04904905, 0.05005005, 0.05105105, 0.05205205, 0.05305305, 0.05405405, 0.05505506, 0.05605606, 0.05705706, 0.05805806, 0.05905906, 0.06006006, 0.06106106, 0.06206206, 0.06306306, 0.06406406, 0.06506507, 0.06606607, 0.06706707, 0.06806807, 0.06906907, 0.07007007, 0.07107107, 0.07207207, 0.07307307, 0.07407407, 0.07507508, 0.07607608, 0.07707708, 0.07807808, 0.07907908, 0.08008008, 0.08108108, 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Uses the scipy library to solve the initial value problem for the system of equations specified in the system_of_equations function, (we currently assume that the initial drug concentrations are zero).

Returns

scipy bunch object

system_of_equations(t, y)

Implements the algebraic ODE formula from the project description in python and evaluates it at a specific time point.

Parameters

• t – point in time, only relevant if you have a continuous dosing protocol

• y – value from which the ODE expression is calculated

Returns

derivative of drug concentrations with respect to time

PKModelling text

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