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Galina Bernstein

Senior Director, Clinical Pharmacology


Dr. Bernstein has PhD in Biochemistry with postdoctoral experience in medicinal chemistry, pharmacokinetics, and data analysis. With more than 20 years of experience in the pharmaceutical and biotech industry, Dr. Bernstein gained expertise in multiple therapeutic areas such as immunology, oncology, dermatology, CNS, and others. Her experience includes data analysis and modeling for special populations such as pediatric patients, geriatric patients, oncology patients, and patients with immune diseases and rare diseases. Her analysis experience includes multiple types of drugs, from small molecules to biologics, including biosimilars, gene therapies, gut microbiomes, and vaccines, as well as various routes of administration, from orals to injection and infusion to topicals. Dr. Bernstein has provided clinical pharmacology and pharmacometrics support for over 300 clinical studies.

The results of her research have been presented in over 30 peer-reviewed publications and at scientific conferences such as AAPS, DIA, ASCPT, ASCO-SITC, and others. Dr. Bernstein also volunteers as a scientific reviewer for the European Journal of Pharmaceutical Sciences, where she is a member of the editorial board. Dr. Bernstein has delivered lectures in clinical pharmacokinetics and clinical pharmacodynamics at TOPRA. She holds professional membership at AAPS, ASCPT, and CPS.

At Premier Consulting, Dr. Bernstein provides scientific leadership on the strategy, planning, implementation, and execution of PK/PD and clinical pharmacology in nonclinical and clinical studies. This includes planning IND-enabling PK/TK studies and designing first-in-human strategies. She leads clinical pharmacology for clinical studies and aids in efficient drug development and regulatory decisions by leading all pharmacometric activities to quantify drug, disease, and trial information. She also leads the development of models to describe the relationship between exposure and response for both desired and undesired effects, as well as individual patient characteristics, and the simulation of disease models to describe the relationship between biomarkers, clinical outcomes, and time course of disease.