CERSI Postdoctoral Fellows

Ziran Li, 2024-2027

Ziran Li

Ziran Li got his Ph.D. degree in Clinical Pharmacology from the Huashan Hospital, Fudan University. After graduation, he started his postdoctoral training in bioengineering under the guidance of Prof. Rada Savic at the University of California, San Francisco (UCSF). With a background in data science, clinical pharmacy, and pharmacometrics, he aims to develop and apply machine learning and pharmacokinetics/pharmacodynamics models to improve the efficacy and safety of drug therapy in clinical practice. Currently serving as a CERSI fellow, he aims to learn more new techniques and gain more expertise in clinical pharmacology and regulatory science through a potential FDA collaboration and eventual immersion in the Gilead Sciences Clinical Pharmacology group.

Xujia Zhou, 2024-2026

Xujia Zhou

Xujia Zhou received her Ph.D. in pharmaceutical sciences and pharmacogenomics from UCSF. During her studies, her research focused on elucidating the ontogenic changes of proteins, particularly transporters, at the human blood-brain barrier, and establishing CRISPR-mediated gene therapy for liver disease. Currently, as a CERSI fellow, she has joined Rada Savic’s lab, where she will gain experience in population PK modeling and participate in projects related to developing PKPD models for vulnerable populations. Xujia is eager to learn how the realms of clinical pharmacology and regulatory science lead to the effective and safe delivery of novel medicines to patients. She hopes to leverage her training in transporter biology and population PK modeling to advance clinical study design and drug development, thereby bridging the gap between laboratory research and real-world patient care.

Jordan Guillot, 2023-2026

Jordan Guillot

Jordan is a pharmacist (PharmD) and researcher in pharmacoepidemiology (PhD). Jordan attended Clermont-Ferrand School of Pharmacy in France, where he grew up. This was followed by completing a pharmacy residency with an emphasis on research at the Bordeaux University Hospital. During this time, he pursued a PhD in pharmacoepidemiology, focusing on understanding the characteristics and risks of polypharmacy using national French healthcare claims data (SNDS: Système National des Données de Santé). Enthusiastic to discover new data, Jordan spent a year at Yale as a Fulbright scholar, working with the Veteran Aging Cohort Study (VACS) group to study polypharmacy in US veterans. After his Fulbright, he returned to Bordeaux University Hospital in France as a hospital-university assistant (AHU) while collaborating with the VACS group.

Motivated to expand his knowledge in generating Real World Evidence, he was awarded the CERSI/Gilead fellowship in Regulatory Science. Currently, he collaborates with Dr. Atul Butte on utilizing Machine Learning and Large Language Models to predict adverse events of CAR T cell therapies. Additionally, he works with Dr. Vivek Rudrapatna on predicting the progression of Metabolic Dysfunction-Associated Steatohepatitis (MASH) towards harmful outcomes. This is achieved by analyzing real-world data collected from UCSF and other University of California hospitals. He will soon begin his rotation at Gilead Sciences in the Biomarker and Molecular Epidemiology team. His focus will be to continue his work on MASH and contribute to other translational projects. After completing this rotation, he plans to further his fellowship by participating in a research project at the FDA that involves real-world evidence.

Annamarie Bustion, 2023-2025

Annamarie Bustion

Annamarie Bustion received her PhD in Pharmaceutical Sciences and Pharmacogenomics from UCSF. Under the primary mentorship of Katie Pollard, and in collaboration with Peter Turnbaugh and Russ Altman, Annamarie developed and validated a novel computational tool (SIMMER) that identified previously unknown bacterial genes responsible for drug metabolism in the human gut. This thesis work helped explain interindividual variation in drug response due to gut microbiome-mediated drug metabolism, but the effects of host versus microbial metabolic machinery could be further disentangled through the application of pharmacokinetic modeling. For this reason, Annamarie next studied with Rada Savic in order to develop research skills in nonlinear mixed effects modeling. During the first year of her CERSI fellowship with the Savic lab, Annamarie developed novel methods for predicting extent of antibiotic penetration into hard-to-treat sites of Tuberculosis (TB), and for modeling the emergence of bacterial resistance to TB drugs in the context of regimen.

One of Annamarie’s career goals is to improve drug-candidate investigations by bringing her expertise in pharmacomicrobiomics (the study of bacterial influence on drug disposition) to the arena of drug development. So far she has built an extensive background in microbiology, pharmacometrics, chemoinformatics, and machine learning. Next, during her upcoming CERSI year with Genentech’s Clinical Pharmacology modeling and simulation team, she will gain pharmacometrics research experience in the context of clinical drug development.

Ségolène Siméon, 2021-2024

Ségolène Siméon

Ségolène Siméon is a postdoctoral fellow working at Genentech, in the Clinical Pharmacology group. She completed her PharmD with a specialization in pharmacometrics at Paris Descartes University. For her PhD research, Ségolène studied the developmental toxicity of zebrafish embryo exposed to teratogen compounds, with the development of two mathematical models. During her first year as a CERSI fellow at UCSF in Savic Lab, she worked on dosing regimen optimization in young malnourished children with malaria disease and studying the malnutrition impact on treatment failure with real world data. Simulations allowed to inform that adjustments must be done for at risk populations from the actual dosing regimen recommendations. She also developed a PKPD model to determine which dosing regimen would allow the best improvement of tuberculosis infection recovering indicators. For these UCSF projects, two papers are in progress. During the second year of the fellowship at Genentech, Ségolène is pursuing her research in the clinical pharmacology team to propose dosing for new indication of drugs and in the modeling and simulation team to work on Crohn’s disease modeling. As a CERSI scholar, she is developing her modeling skills and apply them to the different phases of drug clinical development. She will also learn about drug development protocol and clinical study design.

Huy Ngo, 2020-2022

Huy Ngo

Huy Ngo received a Pharm.D. from Massachusetts College of Pharmacy and Health Sciences and a Ph.D. from University of Kentucky. Subsequently, Huy started his postdoctoral training in transporter biology under the mentorship of Prof. Kathy Giacomini at University of California, San Francisco (UCSF). Huy hopes to leverage his clinical pharmacy and transporter biology training to advance methods in clinical pharmacology study design and drug assessment. As a CERSI fellow, he had the opportunity to develop a population pharmacokinetics model to optimize rifampicin dosing under the guidance of Prof. Rada Savic at UCSF. He also contributed to the design of a clinical study to assess the impact of an excipient on drug absorption under the supervision of Prof. Kathy Giacomini. Currently, Huy is completing his industry rotation in the clinical pharmacology department at Genentech.

Obi Okafor, 2017-2019

Obi Okafor

Obi Okafor is originally from Los Angeles, California. He completed his Doctorate of Pharmacy at Howard University in Washington DC. As a student, he spent time researching the effects of non-cardiac drugs on cardiac rhythm. During his final year, he completed a regulatory science project at the FDA involving the use of gadolinium in MRI based contrast agents. At UCSF, Obi hopes to train under Dr. Kathleen Giacomini on emerging regulatory science challenges surrounding excipient use in generic drugs. Obi believes the CERSI fellowship will be a great opportunity and is curious to witness how best to integrate regulation in science to really drive innovation. His professional interests include patient advocacy and evaluating the current role of biosimilars in healthcare as therapeutic alternatives. In his spare time Obi enjoys watching sports, spending time with family and friends and catching up on sleep.

Kathy Cheung, 2016-2019

Cheung
Kathy Cheung

Kathy Cheung received her Pharm.D. degree from the University of California, San Francisco in 2016. A student pharmacist in the pharmaceutical sciences pathway, she completed a pharmacogenomics research project that aimed to elucidate the genetic factors that are associated with the suboptimal therapeutic response to allopurinol in gout patients. Kathy is currently working on a regulatory science project on medical countermeasures under the direct mentorship of Dr. Kathleen Giacomini. Specifically, she is interested in characterizing the differences in the expression levels and activities of renal membrane transporter in special populations, and how such differences will affect drug absorption and disposition. As a UCSF-Stanford CERSI postdoctoral fellow, Kathy is curious to learn how the academia, industry and regulatory agencies work together to translate health care innovations and scientific findings to practical applications in patient care while ensuring safety and efficacy.

Jennifer Wilson, 2016-2019

Jennifer Wilson

Jennifer L. Wilson is an assistant professor of bioengineering at the University of California, Los Angeles leading the Lab for the Understanding of Network Effects (LUNE). The group uses computational models of cellular protein interactions to model drug-induced effects – both for drug efficacy and potential side effects – for untreated diseases.

During her CERSI fellowship, she studied how drug efficacy and side-effects were associated with cellular protein interactions using computational models. She built the PathFX algorithm in conjunction with Russ Altman (Stanford) and the Genomics and Targeted Therapy Group at the FDA and deployed the algorithm as an ORISE fellow at the FDA to predict drug side-effects for drugs in development. Jen interned with the Genentech Regulatory and Clinical Pharmacology groups where she supported the Tecentriq program and later used predictive modeling to understand toxic side-effects for new anti-cancer drugs in development. Her CERSI fellowship provided a deeper understanding of the challenges of drug development and further motivated her to return to academia to improve computational models of drug-induced effects.

Publications related to this work include:

  • Wilson JL, Steinberg E, Racz R, Altman RB, Shah N, Grimes K. A network paradigm predicts drug synergistic effects using downstream protein-protein interactions. CPT Pharmacometrics Syst Pharmacol. 2022 Oct 6. doi: 10.1002/psp4.12861. Epub ahead of print. PMID: 36204824.
  • Wilson JL, Wong M, Stepanov N, Petkovic D, Altman R. PhenClust, a standalone tool for identifying trends within sets of biological phenotypes using semantic similarity and the Unified Medical Language System metathesaurus. JAMIA Open. 2021 Sep 15;4(3):ooab079. doi: 10.1093/jamiaopen/ooab079. PMID: 34541463; PMCID: PMC8442701.
  • Wilson JL, Cheung KWK, Lin L, Green EAE, Porrás AI, Zou L, Mukanga D, Akpa PA, Darko DM, Yuan R, Ding S, Johnson WCN, Lee HA, Cooke E, Peck CC, Kern SE, Hartman D, Hayashi Y, Marks PW, Altman RB, Lumpkin MM, Giacomini KM, Blaschke TF. Scientific considerations for global drug development. Sci Transl Med. 2020 Jul 29;12(554):eaax2550. doi: 10.1126/scitranslmed.aax2550. PMID: 32727913; PMCID: PMC8158457.
  • Wilson JL, Lu D, Corr N, Fullerton A, Lu J. An in vitro quantitative systems pharmacology approach for deconvolving mechanisms of drug-induced, multilineage cytopenias. PLoS Comput Biol. 2020 Jul 23;16(7):e1007620. doi: 10.1371/journal.pcbi.1007620. PMID: 32701980; PMCID: PMC7402526.
  • Wilson JL, Wong M, Chalke A, Stepanov N, Petkovic D, Altman RB. PathFXweb: a web application for identifying drug safety and efficacy phenotypes. Bioinformatics. 2019 Nov 1;35(21):4504-4506. doi: 10.1093/bioinformatics/btz419. PMID: 31114840; PMCID: PMC6821302.
  • Adeniyi O, Ramamoorthy A, Schuck R, Sun J, Wilson J, Zineh I, Pacanowski M. An Overview of Genomic Biomarker Use in Cardiovascular Disease Clinical Trials. Clin Pharmacol Ther. 2019 Oct;106(4):841-846. doi: 10.1002/cpt.1473. Epub 2019 Jun 20. PMID: 31002380.
  • Wilson JL, Racz R, Liu T, Adeniyi O, Sun J, Ramamoorthy A, Pacanowski M, Altman R. PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development. PLoS Comput Biol. 2018 Dec 7;14(12):e1006614. doi: 10.1371/journal.pcbi.1006614. PMID: 30532240; PMCID: PMC6285459.
  • Wilson JL, Altman RB. Biomarkers: Delivering on the expectation of molecularly driven, quantitative health. Exp Biol Med (Maywood). 2018 Feb;243(3):313-322. doi: 10.1177/1535370217744775. Epub 2017 Dec 3. PMID: 29199461; PMCID: PMC5813871.
  • Wilson JL. A scientist engineer's contribution to therapeutic discovery and development. Exp Biol Med (Maywood). 2018 Oct;243(14):1125-1132. doi: 10.1177/1535370218813974. Epub 2018 Nov 20. PMID: 30458646; PMCID: PMC6327370.