@article {Bergman2022.09.12.507681, author = {Daniel Bergman and Lauren Marazzi and Mukti Chowkwale and Deepa Maheshvare M and Supriya Bidanta and Tarunendu Mapder and Jialun Li}, title = {PhysiPKPD: A pharmacokinetics and pharmacodynamics module for PhysiCell}, elocation-id = {2022.09.12.507681}, year = {2022}, doi = {10.1101/2022.09.12.507681}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Pharmacokinetics and pharmacodynamics are key considerations in any study of molecular therapies. It is thus imperative to factor their effects in to any in silico model of biological tissue involving such therapies. Furthermore, creation of a standardized and flexible framework will benefit the community by increasing access to such modules and enhancing their communicability. PhysiCell is an open source physics-based cell simulator, i.e. a platform for modeling biological tissue, that is quickly being adopted and utilized by the mathematical biology community. We present here PhysiPKPD, an open source PhysiCell-based package that allows users to include PKPD in PhysiCell models.Availability \& Implementation The source code for PhysiPKPD is located here: https://github.com/drbergman/PhysiPKPD.Competing Interest StatementTM is an employee of Bristol-Myers Squibb.ABMagent-based modelMOAmechanism-of-actionPDpharmacodynamicsPKpharamcokinetics}, URL = {https://www.biorxiv.org/content/early/2022/09/15/2022.09.12.507681}, eprint = {https://www.biorxiv.org/content/early/2022/09/15/2022.09.12.507681.full.pdf}, journal = {bioRxiv} }