Key result
Pharmacodynamic modeling techniques based on Hill equations can simulate single-agent and combination regimen effects to relate multiparametric effects to clinical immunosuppressant concentrations.
Computational algorithms and pharmacodynamic modeling offer potential for customizing immunosuppressant drug therapy in transplant recipients.
Immunosuppressant drug toxicity currently competes with acute rejection, as the major cause of efficacy failure of potent new agents in clinical transplantation. The development of mechanistic drug targets as surrogate endpoints for use in the clinic has been facilitated by fluorescent imaging techniques which measure multiple cytokines and cell surface receptors on stimulated (peripheral blood) lymphocyte responses. However, the promise of delivering customized drug therapy to the transplant recipient remains unfulfilled. In this brief review, computational algorithms that can relate multiparametric effects to clinical drug concentrations of immunosuppressants are discussed. Based on Hill equations, these pharmacodynamic modeling techniques have been used to simulate single-agent effects, combination regimen effects, as well as the individual response to combination regimens. The potential implications of these models crystallize the clinical challenges confronting practitioners of clinical, post-transplant immunosuppression.
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Rakesh Sindhi (2004) conducted a review in Clinical transplantation. Pharmacodynamic modeling techniques (computational algorithms) was evaluated. Pharmacodynamic modeling techniques based on Hill equations can simulate single-agent and combination regimen effects to relate multiparametric effects to clinical immunosuppressant concentrations.
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