Sachita Swamy

Data Management in Healthcare

Introduction to Health Data Analytics

- Contributed to the forefront of mRNA therapeutics development. - Leveraged expertise in statistical methodologies, PK/PD analysis, and database management to drive evidence-based decisions and optimize drug development strategies. 1. Statistical v/s PKPD Modelling Comparison for Dose Finding: Applied statistical methodologies using MCP-Mod for dose-response and exposure-response analysis in phase II clinical trials. Instrumental in estimating target doses, shaping the design of subsequent Phase III trials. 2. Non-Compartmental Analysis for PK/PD using various R packages, WinNonLin and Pumas AI: Executed Non-Compartmental Analysis to provide insights into drug behavior, enhancing data-driven decision-making in drug development. 3. Building a Database Query and R shiny Dashboard for QSP nonclinical/preclinical data: Spearheaded statistical analysis of preclinical and QSP data, resulting in a streamlined database. Contributed to the development of an interactive R Shiny dashboard, improving data accessibility. 4. Allometry principle and scaling factors meta-analysis of small molecules V/S mRNA modalities: Conducted literature reviews and meta-analysis on allometric scaling principles, guiding first-in-human dose selection for mRNA programs. Core Responsibilities: - Conducted nonlinear mixed effects modeling and simulation analyses in R and Pumas, contributing to the characterization of population PK. - Established dose-response and exposure-response analyses for informed clinical pharmacology recommendations. - Collaborated with multi-disciplinary project teams, interpreting pharmacometric outcomes and proposing data-driven decisions to clinical pharmacology leadership.

- Developed and executed quality control processes for phase I-IV clinical trial data management, including discrepancy identification, query generation, and resolution tracking in Veeva Vault. - Reviewed adverse event data and ensured protocols were followed per standard operating procedures for optimal subject safety. - Collaborated with clinical operations and data management teams to enhance data quality, enforce protocol compliance, and effectively manage study budgets for three projects. - Partnered cross-functionally to accelerate availability of clean, complete data to support evidence-based decision making for clinical trials. - Communicated with study sites to resolve data queries and discrepancies to ensure integrity of clinical trial data.

- Gained expertise in statistical analysis of healthcare data; interpreted results to derive insights on treatment patterns, outcomes, and risks. - Established skills in planning data collection protocols, cleaning, quality control, and standardization to ensure reliable data for analysis. - Presented data analysis methodologies, results, and recommendations through visually engaging reports and presentations to multidisciplinary teams.

working on a project in cardiac catheterization lab

• Conducted research on dopamine D1 receptor selective ligands and neuro-behavioral evaluation, utilizing Gi and Gs coupled GPCR techniques and qPCR for gene analysis. • Evaluated five drug candidates, gaining insights into neuro-behavioral outcomes and gaining assay development skills for the glosensor cAMP assay. • Proficient in cell culture, including passage and transfection, and utilized fluorescence microscopy and analytical ultracentrifugation for analysis. • Developed skills in neuroscience, cell-based assays, and advanced laboratory techniques relevant to pharmacology and neuroscience.

As a summer research fellow, I worked on a project to investigate the mechanism of action of cancer immunotherapy drugs using essential laboratory techniques of molecular biology. My tasks included: - Designing and conducting in vitro cell-based and molecular biology assays, such as qPCR, ELISA, and Western blot, to measure the expression of immune-related genes and proteins in cancer cells. - Performing statistical analysis of the experimental data using R and Excel, and interpreting the results to derive insights on the treatment patterns, outcomes, and risks of the drugs. - Presenting the data analysis methodologies, results, and recommendations through visually engaging reports and presentations to multidisciplinary teams, including senior researchers and mentors. Through this project, I gained expertise in molecular biology, data analysis, and immunology, and contributed to the advancement of cancer immunotherapy research.