Prasad Chodavarapu

Looking forward to the session at AIPM today. I'm planning to show in action, Aganitha Igniva™ agents for: hypothesis validation, target elucidation, protocol generation, MD results analysis, listening to voices of patients, HCPs and KOLs, and much more.

10.09.2025 20:33 — 👍 0    🔁 0    💬 0    📌 0

I’ve seen firsthand how many painful iterations multi-disciplinary teams go through to decode the biology hidden in #SingleCell #Omics data.

There has to be a faster way — one built for better collaboration, powered by #AI and #LLMs.

#DISTILL is our shot at doing this right.

23.06.2025 21:28 — 👍 0    🔁 0    💬 0    📌 0

If we’re to distribute the fruits of modern #science to all of humanity, we must find ways to scale access to expertise. #AI can be a powerful enabler on this path — augmenting human insight, accelerating development, and broadening accessibility.

28.05.2025 20:26 — 👍 0    🔁 0    💬 0    📌 0

That’s probably it! Era of manual programming of software may now be in the past.

23.05.2025 23:28 — 👍 1    🔁 1    💬 0    📌 0

Scaling Large Language Models for Next-Generation Single-Cell Analysis Single-cell RNA sequencing has transformed our understanding of cellular diversity, yet current single-cell foundation models (scFMs) remain limited in their scalability, flexibility across diverse ta...

Glad to see multi-cell, multi-modal model attempted.

C2S-scale extends Cell2Sentences (C2S), a previous #virtualcell model, to 27B parameters, training on a 1B token Multi-modal dataset with a context length of 8192 (this needs to increase too).

www.biorxiv.org/content/10.1...

18.04.2025 15:16 — 👍 0    🔁 0    💬 0    📌 0

TEDDY: A Family Of Foundation Models For Understanding Single Cell Biology Understanding the biological mechanism of disease is critical for medicine, and in particular drug discovery. AI-powered analysis of genome-scale biological data hold great potential in this regard. T...

Reflecting on #virtualcell: Given that no cell is an island, what's the chance of inferring biology looking at just a single cell's transcriptome? As a recent preprint (arxiv.org/abs/2503.03485) said, "After all, we do not have healthy or diseased annotations for individual cells." #singlecell

18.04.2025 11:54 — 👍 1    🔁 0    💬 1    📌 0

Talk to us at #PMWC25 to see demos and know more first hand.

www.aganitha.ai/pmwc25/

05.02.2025 14:55 — 👍 0    🔁 0    💬 0    📌 0

In the panel discussion at #BiologicsWorkshop2025 in Goa last week, discussing #AI for #Bioprocess. Consensus was that AI adoption for meeting operational needs is proving easier than adoption for process optimisation given the regulated nature of bioprocesses.

04.02.2025 05:36 — 👍 1    🔁 0    💬 0    📌 0

Loved the interactions at #BiologicsWorkshop2025 in Goa last week. I shared three case studies illustrating convergence of #AI and #DeepScience in the modeling and optimization of synthesis processes for mAb, mRNA and Gene therapies.

04.02.2025 05:35 — 👍 0    🔁 0    💬 0    📌 0

Beyond the Hype: Al Case Studies Accelerating Biopharma R&D Speaker: Vikram Duvvoori CEO & Co-Founder Aganitha Al Feb 5, 11:00 am, Showcase Track SI Precision Medicine World Conference (PMWC - 2025) Dates: 5 - 7 February 2025 Venue: Santa Clara Convention Center Booth: #B722

📢 Join us at #PMWC25 to talk about AI in BioPharma R&D

Vikram Duvvoori, CEO of Aganitha.ai, will be presenting case studies showing how #GenerativeAl & in silico modeling are mining insights from deep science to accelerate #BioPharma R&D. Event details in the poster below. See you there.

22.01.2025 12:36 — 👍 2    🔁 1    💬 0    📌 0

Delighted to release this preprint - it was overdue. While a lot of advances happened in the meanwhile in #GenAI and protein language models, Autograd powered numerical optimization provides a direct approach to build upon datasets generated in large directed evolution screens. 🧬 🧪🧶🖥️

12.12.2024 05:34 — 👍 1    🔁 0    💬 0    📌 0