Sanatan Panda

Overall CPI 9.57/10, Courses 8.99/10, Project 10/10. Degree conferred Aug 2023

Relevant courses: Biostatistics, Computational Biology, Genomics and Proteomics, Mathematics for Biologists, Economic Analysis for Public Policy, Clinical Data Management.

CGPA 8.14/10. Awarded with Honours

All India Rank 46, score 558

Global Customer Insights Associate Lead, Data Analytics and AI Strategy. Bangalore

• Global customer and market insights for cardiovascular lead molecules using patient-level data (IQVIA LRx, LAAD, MIDAS).
• Owns Patient Data Warehouse analytics and BI platform (Snowflake SQL, Power BI, Databricks, Python).
• Builds GenAI and agentic AI workflows for insight generation and automated reporting.

Associate Consultant (Aug 2024 to Jun 2026); Associate (Jul 2023 to Aug 2024). Gurgaon

• RWE study design for an FDA-approved first-in-class oncology targeted therapy: observational framework across 8 study designs with codelists, SAP, and endpoint logic.
• Patient treatment journey solution built from inception on US open claims data.
• Revenue forecasting model with 100+ parameters for 6 pipeline oncology molecules.
• Market access analytics: payer evidence, formulary and coverage gaps, prior authorization patterns.
• Field force strategy: HCP targeting, sizing, territory alignment, incentive compensation.
• 5-module Power BI platform (patient landscape, brand analytics, HCP recruitment, burden of illness, longitudinal analysis), adopted firm-wide.
• Authored a 43-page internal RWE methods guide (propensity scores, IPTW, survival analysis, estimands, HEOR).
• Mentored a 10-member team. Rated Exceptional (4/4), March 2026.

Business Analyst. Bangalore

• Prescriber classification ML model segmenting HCPs by longitudinal prescription behavior (SQL, Alteryx, PySpark).

Innovation Think Tank

• Selected among top 50 teams nationally; prototype for 3D MRI reconstruction.

In Silico Drug Discovery Intern

• Virtual screening of 500 COVID-19 drug candidates (AutoDock, PyMol, ADMET, QSAR).

M.Tech thesis, IIT Bombay. Supervisor: Prof. Prakriti Tayalia

• Public bulk RNA-seq from PBMCs. Samples after QC: AS 23, RA 63, SLE 173, T1D 137, Healthy 43.
• Pipeline: Trimmomatic, HISAT2 (hg38), samtools, featureCounts on the IIT Bombay Spacetime HPC cluster (Linux).
• DESeq2 normalization and differential expression; Gene set enrichment analysis (GSEA); Protein-protein interaction and gene regulatory networks; Principal component analysis (PCA).
• Models: Logistic regression, SVM, Ensemble model, ANN. Best AUC by disease (ANN): RA 0.97, SLE 0.80, T1D 0.80, AS 0.75. Evaluated on an external test set.

MTP-1, IIT Bombay

Expression analysis of LMNA and SUN2; Survival cut-off analysis; Comparison across nodal stage; Comparison across molecular subtypes.

B.Tech thesis, NIT Rourkela. Supervisor: Prof. J Sivaraman

A missed blocker (false negative) carries a cardiotoxicity risk downstream, so sensitivity and AUC were prioritized over raw accuracy.

Submitted. 5th author.