Workflows reflect the scientific and quality questions behind a robust generic product.
Company & leadership
Decision intelligence for stronger generic products.
BayesPK Generics connects pharmaceutical sciences, product economics, quality thinking, and applied AI across formulation, scale-up, bioequivalence, and ANDA readiness.
Reference-product understanding, formulation, scale-up, BE, and evidence stay linked.
AI and automation are used to clarify options, expose risk, and reduce repetitive work.
Leadership
Built by people who connect science, software, and execution.
The team combines pharmaceutical sciences, Bayesian modeling, machine learning, and product engineering to make complex generic-development decisions easier to reason about.
UR
Gunda Upendar Rao
Co-founder & CTOArchitect of the BayesPK platform, leading product strategy, model-to-API infrastructure, pharmaceutical decision workspaces, and scalable engineering for development intelligence.
A serial entrepreneur with deep expertise in pharmaceutical sciences, he has founded and built ventures across pharmaceutical technology and education.
Pharmaceutical sciencesProduct strategyModel-to-API systemsEntrepreneurship
YK
Yashwant Kumar Yarramsetty
AI/ML EngineerBuilds machine-learning capabilities for development forecasting, evidence synthesis, and decision support across the BayesPK platform.
His work connects Bayesian methods, natural-language processing, and applied AI with practical pharmaceutical workflows and reviewable outputs.
Bayesian modelingApplied machine learningNLPEvidence synthesis
AY
Anvesh Yerramsetty
AI/ML EngineerContributes to the engineering and evaluation of AI-assisted pharmaceutical workflows, with emphasis on dependable data handling and reviewable system behavior.
His work supports the translation of machine-learning prototypes into bounded product capabilities that keep assumptions, limitations, and human review visible.
AI/ML engineeringData workflowsModel evaluationProduct integration
Our approach
Build the product story before the submission story.
Generic development becomes expensive when connected decisions are reviewed in isolation.
Reference-product understanding, excipient selection, process choices, dissolution behavior, scale-up, BE, quality, and ANDA evidence all influence one another.
BayesPK keeps those tradeoffs visible while changes are still practical.
Understand the reference product
Structure available evidence, critical attributes, and development assumptions.
Design with tradeoffs visible
Compare formulation, process, dissolution, cost, and quality implications together.
De-risk scale-up and BE
Surface sensitivity and evidence gaps before pilot batches and pivotal studies.
Carry reasoning into the ANDA
Reuse the development evidence chain for review, submission, and lifecycle decisions.
Platform focus
A connected path from opportunity to ANDA readiness.
Each workspace answers a focused question while preserving handoffs across development teams.
Reference-product intelligence
Structure reverse engineering, QTPP, product complexity, and opportunity context.
Formulation & QbD
Connect excipients, process choices, safe spaces, dissolution, and product economics.
Scale-up & quality
Review process sensitivity, transfer risk, validation, stability, and quality operations.
BE & ANDA evidence
Keep dissolution, bioequivalence, development rationale, and submission readiness connected.
Bayes Pharma.ai portfolio
Focused products for distinct development paths.
Generic and innovator drug development share scientific foundations, but their workflows and evidence strategies deserve clear product boundaries.
BayesPK Generics
Connected formulation, reverse engineering, scale-up, bioequivalence, quality, and ANDA readiness.
Explore BayesPK GenericsBayes Pharma.ai Innovator
Decision intelligence from candidate discovery through model-informed development and submission-ready regulatory evidence.
Meet Innovator Start a conversation
Contact BayesPK Bring one difficult generic-development decision.
See how BayesPK can connect the product question, tradeoffs, evidence, and next action in one focused workflow.