Projects

This portfolio showcases ongoing projects using PKRxiv datasets to answer clinically relevant questions, develop and validate models, and generate new evidence. Click a project to see the datasets used, the primary aim, and the lead investigator.

PBPK modelling of maraviroc dosing during pregnancy and rifampin co‑administration

Requested Data: Angela Colbers, Brookie Best, Stein Schalkwijk, Jiajia Wang, Alice Stek, Carmen Hidalgo Tenorio, David Hawkins, Graham Taylor, Regis Kreitchmann, Sandra Burchett, Annette Haberl, Kabamba Kabeya, Marjo van Kasteren, Elizabeth Smith, Edmund Capparelli, David Burger, & Mark Mirochnick. (2025). Maraviroc Pharmacokinetics in HIV-1–Infected Pregnant Women (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0014: https://doi.org/10.58033/FJPQ-EM93

Primary Aim: To validate a physiologically based pharmacokinetic (PBPK) model of maraviroc in pregnancy and to predict optimal maraviroc dosing in pregnant individuals during co‑administration with rifampin.

Lead Investigator: Nguyen Dat

Affiliation: Department of Clinical Pharmacology, Mahidol‑Oxford Research Unit, Thailand

Physiologically based pharmacokinetic modeling of rilpivirine to support dose optimization in pregnant women living with HIV

Requested Data: Anna H. Tran, Brookie M. Best, Alice Stek, Jiajia Wang, Edmund V. Capparelli, Sandra K. Burchett, Regis Kreitchmann, Kittipong Rungruengthanakit, Kathleen George, Tim R. Cressey, Nahida Chakhtoura, Elizabeth Smith, David E. Shapiro, & Mark Mirochnick. (2025). Pharmacokinetics of Rilpivirine in HIV-Infected Pregnant Women (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0012: https://doi.org/10.58033/2988-2541

Primary Aim: To develop and validate a PBPK model of rilpivirine and evaluate dose optimization strategies in pregnant women living with HIV.

Lead Investigator: Jeremiah D. Momper

Affiliation: Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California - San Diego, USA

Population pharmacokinetic modelling and limited sampling strategy development for raltegravir in pregnancy

Requested Data: D. Heather Watts, Alice Stek, Brookie M. Best, Jiajia Wang, Edmund V. Capparelli, Tim R. Cressey, Francesca Aweeka, Patty Lizak, Regis Kreitchmann, Sandra K. Burchett, David E. Shapiro, Elizabeth Hawkins, Elizabeth Smith, & Mark Mirochnick. (2025). Raltegravir Pharmacokinetics During Pregnancy (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0013: https://doi.org/10.58033/3W7Y-FW08

Primary Aim: To develop a population pharmacokinetic (popPK) model of raltegravir using NONMEM and to derive a limited sampling strategy to support therapeutic drug monitoring in pregnant patients.

Lead Investigator: Ana Flávia Mendes Batista

Affiliation: General Hospital of Ribeirão Preto Medical School, University of São Paulo, Brazil

Utilising clinical pharmacokinetic data to reassess a legacy pregnancy PBPK model for efavirenz

Requested Data: Tim R. Cressey, Alice Stek, Edmund Capparelli, Chureeratana Bowonwatanuwong, Sinart Prommas, Pannee Sirivatanapa, Prapap Yuthavisuthi, Chanon Neungton, Yanling Huo, Elizabeth Smith, Brookie M. Best, & Mark Mirochnick. (2025). Efavirenz Pharmacokinetics During the Third Trimester of Pregnancy and Postpartum (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0011: https://doi.org/10.58033/QXYN-NX97Oluwasegun Eniayewu, Uche Azuka, Jonah Ogah, Ebunoluwa Adejuyigbe, Oluseye Bolaji, & Adeniyi Olagunju. (2025). Pharmacogenetics of Efavirenz Exposure in Cervicovaginal Fluid during Pregnancy and Postpartum (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0010: https://doi.org/10.58033/G748-JP07A Olagunju, O Bolaji, A Amara, L Else, O Okafor, E Adejuyigbe, J Oyigboja, D Back, S Khoo, & A Owen. (2025). Pharmacogenetics of pregnancy‐induced changes in efavirenz pharmacokinetics (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0001: https://doi.org/10.58033/NMMY-PR11

Primary Aim: To evaluate the performance of an existing efavirenz pregnancy PBPK model by integrating newly curated clinical PK data, thereby illustrating its utility.

Lead Investigator: Shakir Atoyebi

Affiliation: Department of Biochemistry, Cell and Systems Biology, University of Liverpool, Liverpool, UK

Real‑world analysis of antiviral drug exposure variability and adverse outcomes in pregnancy

Requested Data: Adeniyi Olagunju, Saye Khoo, & Andrew Owen. (2025). Pharmacogenetics of Nevirapine Excretion into Breast Milk and Infants’ Exposure Through Breast Milk Versus Postexposure Prophylaxis (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0006: https://doi.org/10.58033/EG8J-V638

Primary Aim: To explore variability in antiviral drug exposure and associated adverse outcomes during pregnancy using real‑world data, identify sources of variability and evidence gaps, and benchmark findings against a Portuguese hospital cohort to support safer, more effective dosing strategies.

Lead Investigator: Bárbara Costa

Affiliation: University of Porto, Portugal

Benchmarking PK model fitting and cross-validation workflows in Phoenix WinNonlin vs nlmixr2 (R)

Requested Data: Abdulafeez Akinloye, Timothy Oyedeji, Oluwasegun Eniayewu, Babatunde Adeagbo, Oluseye Bolaji, Steve Rannard, Andrew Owen, & Adeniyi Olagunju. (2025). Atazanavir/Ritonavir Increased Tizoxanide Exposure from Oral Nitazoxanide through Pharmacokinetic Interaction in Healthy Volunteers (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0003: https://doi.org/10.58033/W4VY-7Q28

Primary Aim: To practice PK data fitting and model cross-validation and to compare the performance of models developed using Phoenix WinNonlin (WNL) and nlmixr2 in R.

Lead Investigator: Ivy Wu

Affiliation: N/A

Machine learning prediction of efavirenz exposure using a limited sampling strategy

Requested Data: A Olagunju, O Bolaji, A Amara, L Else, O Okafor, E Adejuyigbe, J Oyigboja, D Back, S Khoo, & A Owen. (2025). Pharmacogenetics of pregnancy‐induced changes in efavirenz pharmacokinetics (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0001: https://doi.org/10.58033/NMMY-PR11

Primary Aim: To develop and validate machine learning models in R to predict efavirenz plasma exposure from limited sampling time points, improving clinical relevance for personalized dosing.

Lead Investigator: Nathan Nakao

Affiliation: University of São Paulo, Brazil

Machine learning prediction of dolutegravir AUC with external validation and development of a limited sampling strategy

Requested Data: Catriona Waitt, Catherine Orrell, Stephen Walimbwa, Yashna Singh, Kenneth Kintu, Bryony Simmons, Julian Kaboggoza, Mary Sihlangu, Julie-Anne Coombs, Thoko Malaba, Josaphat Byamugisha, Alieu Amara, Joshua Gini, Laura Else, Christie Heiburg, Eva Maria Hodel, Helen Reynolds, Ushma Mehta, Pauline Byakika-Kibwika, … Saye Khoo. (2025). Safety and pharmacokinetics of dolutegravir in pregnant mothers with HIV infection and their neonates: A randomised trial (DolPHIN-1 study) (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0008: https://doi.org/10.58033/P2TT-XC95

Primary Aim: To develop and externally validate machine learning models (SVM, XGBoost, Lasso/Elastic-Net GLMs, Random Forest) for predicting dolutegravir AUC, and—if performance is adequate—to derive a limited sampling strategy using sparse early plasma samples to reduce patient burden while maintaining prediction accuracy/precision

Lead Investigator: Matheus De Lucca Thomaz

Affiliation: University of São Paulo, Brazil

Predicting Concentration of Nevirapine Using a Novel PK/Machine Learning Method

Requested Data: Adeniyi Olagunju, Oluseye Bolaji, Megan Neary, David Back, Saye Khoo, & Andrew Owen. (2025). Pregnancy affects nevirapine pharmacokinetics [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0007: https://doi.org/10.58033/KBJW-QC26

Primary Aim: To develop and evaluate a novel pharmacokinetic/machine learning hybrid model to predict nevirapine concentrations in treated patients, and to compare its precision and predictive performance against a PKPD modeling approach.

Lead Investigator: Elham Haem

Affiliation: Shiraz University of Medical Sciences, Iran

Population PK modelling and limited sampling strategy optimisation for dolutegravir in pregnancy and postpartum

Requested Data: Catriona Waitt, Catherine Orrell, Stephen Walimbwa, Yashna Singh, Kenneth Kintu, Bryony Simmons, Julian Kaboggoza, Mary Sihlangu, Julie-Anne Coombs, Thoko Malaba, Josaphat Byamugisha, Alieu Amara, Joshua Gini, Laura Else, Christie Heiburg, Eva Maria Hodel, Helen Reynolds, Ushma Mehta, Pauline Byakika-Kibwika, … Saye Khoo. (2025). Safety and pharmacokinetics of dolutegravir in pregnant mothers with HIV infection and their neonates: A randomised trial (DolPHIN-1 study) (dataset) [Data set]. PKRxiv, University of Liverpool. PKRxivStudy-0008: https://doi.org/10.58033/P2TT-XC95

Primary Aim: To develop a population pharmacokinetic (popPK) model of dolutegravir using a limited sampling strategy (LSS) approach, in order to identify optimal sampling times and improve therapeutic drug monitoring strategies in pregnant and postpartum women.

Lead Investigator: Álef Machado Gomes Pego

Affiliation: University of São Paulo, Brazil