CAMBRIDGE, Mass., Dec 5, 2024 --- Insilico Medicine (“Insilico”), a clinical-stage generative artificial intelligence (AI)-driven drug discovery company, announced that it has successfully closed the highly anticipated Pharma.AI week webinar series, with over 500 attendees from 63 countries all over the world, witnessing the release of reinforced generative AI platforms, and the highlights are listed below:
Science42: DORA, the AI Agent-based Intelligent Writing Assistant
- Enhanced Agentic Research: The addition of new agents enriches the capabilities of the platform, providing users with more tools to conduct comprehensive research.
- Web Search: The web search functionality allows DORA to access real-time data from the web, and advanced insights from PandaOmics. Try enriching your report a bit more with the new function!
- Generation Transparency: This feature ensures that users can observe the document generation process in real-time, offering full transparency on how the AI crafts and sources information. This improves trust and allows users to understand how their content is being shaped.
PandaOmics, the Target Discovery and Prioritization Engine
- Data Warehouse Update: With the latest update, PandaOmics expanded its database, doubling the clinical trial information to 1 million while introducing enhanced datasets covering omics, publications, grants, patents and knowledge graphs and more. Besides, Insilico’s Data Warehouse is now available, enabling insights on gene-disease associations and evidence-based research with Evidence Graph.
- Self-Service Registration: The platform now comes with flexible subscription plans including monthly, quarterly, and yearly options. A 7-day free trial is available for new users, with significant discounts for academics, which opens up the platform to a broader audience and supports democratization of access to cutting-edge research tools.
Chemistry42, the Generative AI-powered Molecule Generation Platform
- Model Training the New Application: Users can now train models with their own experimental data, and the platform will choose the best model parameters and compute the test metrics automatically.
- Retrosynthesis the New Application: a qualitative tool for discovering synthetic routes for your molecules, it considers chemo-, regio-, and stereoselectivity to generate up to 3 alternative synthetic pathways for small drug-like molecules, providing flexibility in route selection.
Generative Biologics, the AI Tool for De Novo Protein Engineering
- User Data-Based Models Retraining: This feature enables users to train predictive models directly on the platform using their own experimental data, such as affinity or developability properties. These properties can then be leveraged in subsequent prediction and optimization workflows. Users have the flexibility to optimize properties individually or simultaneously, facilitating multi-parameter optimization for more comprehensive results.
- Template-Based Design: A novel template-based peptide generation workflow is introduced. Unlike de novo approaches, this pipeline optimizes existing binders by generating thousands of novel sequences based on provided protein-peptide complexes. Each peptide is then evaluated using our cutting-edge affinity prediction models, enabling you to identify and select candidates that outperform the original binder.
"The recent updates to Pharma.AI represent a major leap forward, as we keep integrating cutting-edge AI models and dataset expansion," says Petrina Kamya, PhD, Vice President and Global Head of AI Platforms and President of Insilico Medicine Canada. "For example, Generative Biologics has incorporated user data-based model retraining and improved its generative and reward models, achieving an 8% increase in accuracy and a 25% boost in speed. With the power of generative AI, we hope to further streamline the innovation process, in the pharmaceutical industry and beyond."
In 2016, Insilico first described the concept of using generative AI for the design of novel molecules in a peer-reviewed journal, which laid the foundation for the commercially available Pharma.AI platform. Since then, Insilico keeps integrating technical breakthroughs into Pharma.AI platform, which is currently a generative AI-powered solution spanning across biology, chemistry and clinical development. Powered by Pharma.AI, Insilico has nominated 20 preclinical candidates in its comprehensive portfolio of over 30 assets since 2021 and has received IND approval for 10 molecules.
"It is amazing to see how Pharma.AI grew into the comprehensive generative AI platform today, through the endless innovation our team has been striving for," says Alex Zhavoronkov, PhD, Founder and CEO of Insilico Medicine. "Our aspirations are to continue pushing the boundaries of what is possible in drug discovery and scientific breakthrough, making the process faster, more cost-effective, and highly precise. "
In early 2024, Insilico published a Nature Biotechnology paper presenting the entire R&D journey from AI algorithms to Phase II clinical trials of ISM001-055, the company’s lead drug pipeline with AI-discovered target and AI-designed structure. Following that, Insilico has recently announced positive preliminary results from a Phase IIa trial (NCT05938920), where ISM001-055 showed favorable safety and tolerability across all dose levels, as well as dose-dependent response in forced vital capacity (FVC), after only 12 weeks of dosage.
About Insilico Medicine
Insilico Medicine, a global clinical stage biotechnology company powered by generative AI, is connecting biology, chemistry and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers and other modern machine learning techniques for novel target discovery and the generation of novel molecular structures with desired properties. Insilico Medicine is developing breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system diseases, infectious diseases, autoimmune diseases, and aging-related diseases.