Insilico Medicine Launches AI-Driven Sustainability Initiative and Unveils Latest Advances in Pharma.AI Platform at IMGAIA Event

Generative AI has been gaining power these days, transforming a variety of fields from creative arts to healthcare, software development to customer service. Its ability to create content, solve problems, and automate tasks has proven to be a game-changer, paving the way for unprecedented advancements. However, with great power comes great responsibility. As these systems become increasingly sophisticated, the question arises: how can we make them more helpful?

Insilico Medicine(“Insilico”), a clinical-stage generative artificial intelligence (AI)-driven drug discovery company, today hosted IMGAIA, Insilico Medicine generative AI Action, webinar, revealing its Generative Al Benchmarking Initiative for Sustainability, launched new applications including Biology42: PandaOmics Box, Science 42: DORA, and Precious-3 GPT, and updates of its proprietary Pharma.AI platform.

"By maintaining a balanced relationship between human activities and the natural world, sustainability initiatives foster a healthier and more prosperous world for all, and that has always been our first goal since Insilico’s start," says Alex Zhavoronkov, PhD, Founder and CEO of Insilico Medicine. "Today, we hope to enable faster and more accurate scientific discoveries, by providing current and potential researchers with more reliable and more efficient AI tools. Also, our sustainability initiative is likely an industry benchmark, which sets an example illustrating how AI is used for shared welfare."

Climate change is a global emergency that goes beyond national borders. It is an issue that requires international cooperation and coordinated solutions at all levels. The Paris Agreement, signed in 2015 by around 200 countries, sets long-term goals to guide all nations to stabilize climate change by reducing greenhouse gas emissions. AI, as an emerging productivity, certainly opens up more possibilities for realizing this goal.

 At Insilico, we collaborated with Aramco to develop new materials for efficient CO₂ carbon capture and repurpose it for industrial applications. We also partner with Syngenta to develop new products for sustainable agriculture. Based on some initial explorations, we would like to release a "Generative AI Benchmarking Initiative for Sustainability'' to encourage ecosystem partners to join us with cutting edge AI technology and address this global challenge.

 In the past, we have done this for drug discovery with the release of MOSES (in 2018 and then published in a peer-reviewed journal in 2020), which is now highly-cited and it helped many companies in generative AI in chemistry. We believe that as a very independent company out of the petrochemical industry - we would like to be and may be the best platform and arbiter to form such a benchmarking consortium.

Writing research papers is critical for disseminating scientific findings, but it does come with efficiency burdens, particularly for early-career researchers and non-native English speakers. A survey published in Nature in 2018 indicated that approximately 37% of respondents reported that they spend more than 20 hours a week on writing and revising scientific papers. DORA is an intelligence research and writing assistant that integrates multiple AI agents that leverage LLMs and is designed to streamline the process of drafting academic papers and other scientific documents including grant and patent applications, internal research summaries, IND applications, etc. It assists researchers in drafting these types of documents with proper referencing through engineered prompts, proprietary databases, and pre-designed content generation workflows.

To further validate DORA’s abilities, Insilico's developers collaborated with researchers at the University of Copenhagen to submit a paper on medRxiv. The paper drafted by DORA and later manually curated and extended, performs a comparative study about radiotherapy outcomes across brain tumor types, namely Glioblastoma Multiform and Low-Grade Gliomas based on radiotherapy phenotype and expression data from 32 cancer datasets. Insilico plans to further test DORA in multiple types of document generation and launch a free trial version of the AI assistant to the public in late 2024.

AI Efficiency improves the Biomedical Data Interpretation. However, 64% of healthcare providers had concerns about data privacy and security (Frost & Sullivan). Most AI solutions are SaaS-based and reliant on cloud systems, unsuitable for sensitive environments like hospitals, research institutes, and pharmaceutical companies, significantly hindering innovation in medicine and biology.

PandaOmics Box, is an industry-first AI-powered converged research solution that supports localized biological research while ensuring data confidentiality. It Integrates PandaOmics, Insilico’s generative AI-driven biological analysis engine, extensive scientific databases, and advanced hardware systems with state-of-the-art computational power and chip-level confidential computing for secure, offline, on-premise deployments. PandaOmics Box is designed to significantly accelerate innovation in target identification, biomarker discovery, and indication prioritization by organizations with stringent data security requirements, especially hospitals and research institutions.Additionally, the system is equipped with OpenAPI framework, and allows Bioinformatics access to PandaOmics' extensive database and advanced AI algorithms. This feature provides researchers the flexibility to develop their own custom analyses, enabling them to create innovative methods that blend with their proprietary data for deeper insights.

In 2022,  the World Health Organization released the changes it planned to make to International Classification of Diseases (ICD). In the revisions, the diagnosis of “senility” was  replaced with “old age,” which was interpreted as suggesting that old age is a disease in itself. 

Some researchers looked forward to the revision, seeing it as part of the path toward creating and distributing anti-aging therapies. However, new drugs typically take around 10 years and about $2 billion to bring to market. Moreover, less than 10% of new drugs successfully transition from R&D to the clinic. To limit the wasting of time and resources, many researchers have begun utilizing AI-driven drug discovery.

Precious-3 GPT is a pre-trained transformer engine across multi-modal, multi-omics, multi-species for biomedical research. Precious-3 GPT features a novel tokenization and training procedure that has enabled it to extract biomedical information from >2MM omics observations, as well as PubMed text and knowledge graphs. It understands basic aging processes in multiple species and can discover novel protein targets, identify aging and disease treatments, predict biological age using methylation, expression, proteomics data, and blood tests. It also supports the discovery of anti-aging interventions and validates them virtually across multi-species, including mouse, rat, monkey, and human.

Insilico is validating part of the P3GPT's capabilities through Life Star 1, its proprietary automated robotics lab. As a next step, Insilico plans to publish the open source of Precious-3 GPT to encourage industry researchers to join in exploring anti-aging solutions using AI.

Artificial intelligence (AI) has swiftly revolutionized numerous industries, and the life sciences sector is no exception. The growing power and capability of AI present immense opportunities for advancing research and development.
Since its industry-first description of the concept of applying generative AI to drug discovery and development in a peer-reviewed paper in 2016, Insilico has built Pharma.AI, the generative AI-driven platform connecting biology, chemistry, medicine, and science to solve complex challenges in life sciences, by accelerating drug development, enhancing precision medicine and supporting anti-aging research. All the innovative products above are new additions to the Pharma.AI platform.
In the past few years, Insilico has optimized and validated its Pharma.AI platform through internal drug pipeline development and external R&D collaborations. Currently, 10 of the world's top 20 pharmaceutical companies use Pharma.AI. Powered by the platform, Insilico has nominated 18 preclinical candidates in its comprehensive portfolio of over 30 assets since 2021, and has received IND approval for 7 molecules. Recently, the company published a paper in Nature Biotechnology presenting the entire R&D journey of its lead drug pipeline, INS018_055, from AI algorithms to Phase II clinical trials.At Insilico, we are committed to continually expanding the boundaries of AI applications and applying them to all aspects of life science to accelerate drug discovery, empower anti-aging research, and support sustainable development. These new product launches are expected to help life science researchers accomplish their tasks more easily and efficiently. We believe this is the true promise of generative AI.

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. www.insilico.com