AI + Cheminformatics: The Future Career Formula for Drug Discovery & Pharma Innovation
Empowering Chemists with AI-Driven Skills for Modern Pharma Research
Date: 23rd October 2025
Time: 7:00 PM – 8:00 PM IST
Location: Online (Zoom)
Rasayanika successfully hosted the webinar “AI + Cheminformatics: The Future Career Formula for Drug Discovery & Pharma Innovation” on 23rd October 2025, an insightful session designed for students, researchers, and professionals keen to explore the transformative role of AI/ML in chemistry and pharmaceutical innovation. The one-hour live session brought together industry leaders and internal experts to provide a roadmap for building AI-ready skill sets that align with the evolving needs of the global pharma and biotech industries.
Welcome & Introduction
The webinar began with a welcome note by Mrs. Urmimala, who highlighted why AI and Machine Learning (ML) are revolutionizing modern biosciences. She emphasized the growing importance of practical AI/ML experience for research careers and introduced the speakers and session flow, setting the stage for a highly engaging knowledge-sharing session.
- Predictive Chemistry, Where Algorithms Meet Molecules
Speaker: Guest Speaker (External)
About the Speaker
The guest speaker is a leading professional in cheminformatics and AI-driven molecular research, specializing in predictive modelling and computational chemistry applications.
Session Highlights
The session explored the evolution of cheminformatics from basic molecular descriptors to advanced deep learning techniques. Key insights included:
- AI models that predict toxicity, reactivity, and bioactivity before experiments.
- Real-world applications: QSAR modelling, virtual screening, and molecular docking.
- Essential computational concepts: SMILES notation, molecular fingerprints, and graph-based models.
- AI tools empowering chemists: DeepChem, RDKit, and AlphaFold, enabling data-driven discovery rather than trial-and-error experimentation.
Attendees gained a clear understanding of how computational chemistry is accelerating drug discovery and why mastering AI tools is essential for modern chemists.
- The Industry Shift — How Pharma is Investing in AI & What It Means for You
Speaker: Dr. Snigdha Tiwari, Internal Faculty
About the Speaker
Dr. Snigdha Tiwari is an experienced professional in pharmaceutical R&D and computational sciences, specializing in AI integration for drug discovery pipelines.
Session Highlights
Dr. Tiwari provided real-world insights into the growing adoption of AI across global pharmaceutical companies:
- Industry Examples:
- AstraZeneca & Algen Biotechnologies – $555M AI + CRISPR partnership for immunology therapies.
- Takeda Pharmaceuticals – Hiring Associate Directors in Cheminformatics.
- Eli Lilly – Hyderabad Innovation Center to hire 1,500 AI & digital experts by 2026.
- AstraZeneca & Algen Biotechnologies – $555M AI + CRISPR partnership for immunology therapies.
- Global Hiring Trends: 41% YoY increase in AI/ML jobs in India.
- Emerging Roles: AI Chemist, Cheminformatics Data Scientist, Computational Chemist.
- Salary Trends & Demand: Opportunities growing in India and abroad.
Her session highlighted the importance of aligning skillsets with industry needs to secure high-impact roles in computational drug discovery.
- Becoming an AI-Ready Chemist — Skillset & Tools
Speaker: Ms. Shubhi Singh, Internal Faculty
About the Speaker
Ms. Shubhi Singh specializes in AI/ML applications in cheminformatics and in training chemists in computational methods, molecular simulations, and data-driven drug discovery techniques.
Session Highlights
Ms. Singh’s presentation focused on developing practical AI/ML capabilities for chemists:
- Core computational techniques: molecular representations, ML algorithms for QSAR & property prediction, molecular docking, and structure-based modelling.
- AI-based protein and ligand analysis tools.
- Skillsets in demand: data preprocessing, QSAR modelling, docking, Graph Neural Networks (GNNs), and molecular simulations.
- Transitioning from wet-lab to data-lab science: adopting programming, computational reasoning, and data interpretation.
- Future trends: generative AI, digital twins, and autonomous drug design platforms.
Attendees learned how to bridge traditional chemistry skills with AI-driven approaches to stay ahead in research and innovation.
Interactive Q&A and Closing Remarks
The webinar concluded with an engaging Q&A session moderated by Mrs. Urmimala. Participants clarified queries regarding AI tools, career transitions, and industry expectations. The session also introduced Rasayanika’s AI/ML in Cheminformatics Course, starting 28th October 2025, which offers:
- Hands-on experience with DeepChem, RDKit, DiffDock, AlphaFold, and HADDOCK.
- Guided mentorship and research projects (3/6/12 months).
- Certification, placement assistance, and resume/LinkedIn profile guidance
Key Takeaways
- AI + Cheminformatics is transforming the landscape of drug discovery and pharma innovation.
- Proficiency in predictive modelling, QSAR, docking, and AI tools is now essential for chemists.
- The pharma industry is actively investing in AI, creating high-demand roles globally.
- Transitioning from wet-lab to data-lab skills expands career opportunities significantly.
- Certifications, hands-on projects, and mentorship accelerate employability in this emerging domain.
About Rasayanika
Rasayanika is a premier Chemistry education and training platform, dedicated to equipping students, researchers, and professionals with industry-ready skills in Biotechnology, Cheminformatics, AI/ML, and allied domains. Through expert-led courses, live projects, and placement assistance, Rasayanika bridges the gap between academic knowledge and professional success.
Advance Your Career with AI/ML in Chemistry & Cheminformatics
Take your chemical research skills to the next level with Rasayanika’s AI/ML in Chemistry & Cheminformatics Hands-on Industrial Training Program, starting 28th October 2025. This 30-day online course, with optional 3-, 6-, or 12-month project extensions, offers hands-on experience with DeepChem, RDKit, DiffDock, and AlphaFold, along with guidance on research projects and paper publication. Ideal for students, researchers, and industry professionals, the program equips participants to apply AI/ML to drug discovery, cheminformatics, and materials science, making them industry- and research-ready.
