pharmsol 0.27.1

Rust library for solving analytic and ode-defined pharmacometric models.
Documentation 
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use crate::{data::Covariates, simulator::*};

use super::wrap_pmetrics_analytical;

/// Analytical solution for one compartment model.
///
/// # Assumptions
/// - `p` is a vector of length 1 with the value of the elimination constant
/// - `rateiv` is a vector of length 1 with the value of the infusion rate (only one drug)
/// - `x` is a vector of length 1
/// - covariates are not used
pub fn one_compartment(x: &V, p: &V, t: T, rateiv: &V, _cov: &Covariates) -> V {
    let mut xout = x.clone();
    let ke = p[0];

    xout[0] = x[0] * (-ke * t).exp() + rateiv[0] / ke * (1.0 - (-ke * t).exp());
    // dbg!(t, &rateiv, x, &xout);
    xout
}

pub fn pm_one_compartment(x: &V, p: &V, t: T, rateiv: &V, cov: &Covariates) -> V {
    wrap_pmetrics_analytical(x, p, t, rateiv, cov, one_compartment)
}

/// Analytical solution for one compartment model with first-order absorption.
///
/// # Assumptions
/// - `p` is a vector of length 2 with ke and ka in that order
/// - `rateiv` is a vector of length 1 with the value of the infusion rate (only one drug)
/// - `x` is a vector of length 2
/// - covariates are not used
pub fn one_compartment_with_absorption(x: &V, p: &V, t: T, rateiv: &V, _cov: &Covariates) -> V {
    let mut xout = x.clone();
    let ka = p[0];
    let ke = p[1];

    xout[0] = x[0] * (-ka * t).exp();

    xout[1] = x[1] * (-ke * t).exp()
        + rateiv[0] / ke * (1.0 - (-ke * t).exp())
        + ((ka * x[0]) / (ka - ke)) * ((-ke * t).exp() - (-ka * t).exp());

    xout
}

pub fn pm_one_compartment_with_absorption(x: &V, p: &V, t: T, rateiv: &V, cov: &Covariates) -> V {
    wrap_pmetrics_analytical(x, p, t, rateiv, cov, one_compartment_with_absorption)
}

#[cfg(test)]
mod tests {
    use super::super::tests::SubjectInfo;
    use super::{one_compartment, one_compartment_with_absorption};
    use crate::*;
    use approx::assert_relative_eq;

    #[test]
    fn test_one_compartment() {
        let infusion_dosing = SubjectInfo::InfusionDosing;
        let subject = infusion_dosing.get_subject();

        let ode = equation::ODE::new(
            |x, p, _t, dx, b, rateiv, _cov| {
                fetch_params!(p, ke, _v);

                dx[0] = -ke * x[0] + rateiv[0] + b[0];
            },
            |_p, _t, _cov| lag! {},
            |_p, _t, _cov| fa! {},
            |_p, _t, _cov, _x| {},
            |x, p, _t, _cov, y| {
                fetch_params!(p, _ke, v);
                y[0] = x[0] / v;
            },
        )
        .with_nstates(1)
        .with_ndrugs(1)
        .with_nout(1);

        let analytical = equation::Analytical::new(
            one_compartment,
            |_p, _t, _cov| {},
            |_p, _t, _cov| lag! {},
            |_p, _t, _cov| fa! {},
            |_p, _t, _cov, _x| {},
            |x, p, _t, _cov, y| {
                fetch_params!(p, _ke, v);
                y[0] = x[0] / v;
            },
        )
        .with_nstates(1)
        .with_ndrugs(1)
        .with_nout(1);

        let op_ode = ode
            .estimate_predictions(&subject, &crate::parameters::dense([0.1, 1.0]))
            .unwrap();
        let op_analytical = analytical
            .estimate_predictions(&subject, &crate::parameters::dense([0.1, 1.0]))
            .unwrap();

        let pred_ode = &op_ode.flat_predictions()[..];
        let pred_analytical = &op_analytical.flat_predictions()[..];

        println!("ode: {:?}", pred_ode);
        println!("analitycal: {:?}", pred_analytical);

        for (&od, &an) in pred_ode.iter().zip(pred_analytical.iter()) {
            assert_relative_eq!(od, an, max_relative = 1e-4, epsilon = 1.0,);
        }
    }

    #[test]
    fn test_one_compartment_with_absorption() {
        let oral_infusion_dosing = SubjectInfo::OralInfusionDosage;
        let subject = oral_infusion_dosing.get_subject();

        let ode = equation::ODE::new(
            |x, p, _t, dx, b, rateiv, _cov| {
                fetch_params!(p, ka, ke, _v);

                dx[0] = -ka * x[0] + b[0];
                dx[1] = ka * x[0] - ke * x[1] + rateiv[0] + b[1];
            },
            |_p, _t, _cov| lag! {},
            |_p, _t, _cov| fa! {},
            |_p, _t, _cov, _x| {},
            |x, p, _t, _cov, y| {
                fetch_params!(p, _ka, _ke, v);
                y[0] = x[1] / v;
            },
        )
        .with_nstates(2)
        .with_ndrugs(2)
        .with_nout(1);

        let analytical = equation::Analytical::new(
            one_compartment_with_absorption,
            |_p, _t, _cov| {},
            |_p, _t, _cov| lag! {},
            |_p, _t, _cov| fa! {},
            |_p, _t, _cov, _x| {},
            |x, p, _t, _cov, y| {
                fetch_params!(p, _ka, _ke, v);
                y[0] = x[1] / v;
            },
        )
        .with_nstates(2)
        .with_ndrugs(2)
        .with_nout(1);

        let op_ode = ode
            .estimate_predictions(&subject, &crate::parameters::dense([1.0, 0.1, 1.0]))
            .unwrap();
        let op_analytical = analytical
            .estimate_predictions(&subject, &crate::parameters::dense([1.0, 0.1, 1.0]))
            .unwrap();

        let pred_ode = &op_ode.flat_predictions()[..];
        let pred_analytical = &op_analytical.flat_predictions()[..];

        println!("ode: {:?}", pred_ode);
        println!("analitycal: {:?}", pred_analytical);

        for (&od, &an) in pred_ode.iter().zip(pred_analytical.iter()) {
            assert_relative_eq!(od, an, max_relative = 1e-4, epsilon = 1.0);
        }
    }
}