An AI Digital BioClone™ Factory

ThinkingNode Life Science, Inc. is the first AI techbio company to develop Self-Organized Large Reasoning Models™ (SLRM) to generate the most advanced Human Cell Reasoning Foundation Model.

Applied to drug R&D, ThinkingNode's Digital BioClone™ platform can produce the most advanced human digital cell simulations within an hour via a proprietary process, called Digital Cell Differentiation™, to predict and understand cellular behavior and response to drugs for safety, efficacy, and specificity.

As the cell is the fundamental unit of biology, ThinkingNode can create value at multiple points throughout the entire drug R&D process. Unlike most AI drug R&D companies that focus on drug design, ThinkingNode simulates cellular responses to drugs before and after each stage of pharmaceutical R&D to de-risk by providing critical insights for decision-making. ThinkingNode's Digital BioClones have been used for novel target discovery, target validation, biomarker discovery, indication expansion, drug combination, drug comparison, drug response prediction, mechanism of action validation, and patient stratification.

ThinkingNode’s Self-Organized Large Reasoning Models™ (SLRM) have been created based on the second generation of MARS (Macro-connectionist Reasoning Reasoning System). The first generation of MARS was successfully used in Dr. Pham first AI company (acquired by Nasdaq: EPNY for $637M). The SLRMs are built on extensive knowledge bases characterizing cellular structure and function, and then further refined with gene expression data to produce specific Digital BioClones of interest. The result is highly unique, powerful cell simulations which are capable of predicting dynamic cellular responses in an unprecedented, scalable digital platform.

“We’re thrilled to enter this collaboration to advance our oncology drug programs with ThinkingNodeLife.ai’s AI Digital Cell Clone Lab platform. Integrating AI-powered solutions into our research processes aligns with our aim to adopt smarter practices in our R&D, in order to broaden drug application to more cancer types and speed up the time it takes to bring new drugs to patients,” explained Bertrand Ducrey, CEO of Debiopharm. 

Yo Suzuki, PHD / Associate Professor
J. CRAIG VENTER INSTITUTE, SYNTHETIC BIOLOGY - BIOENERGY GROUP

The Whole-Cell-Centric Approach For
Drug R&D

Developing drugs takes 10 years, costs $2.6 billion, and has a 5% success rate — largely due to preclinical animal testing failing to translate to humans.

Beyond animal models: ThinkingNode focuses on patient biopsy, organoid, and tumor xenograft digital simulations to consolidate animal models. This can help drug R&D companies:

1) To better design their drugs by simulating the impacts of the off-targets and identify their side-effects on the whole-cell.

2) To rank their compounds for various indications.

3) To identify the best models for preclinical testing (cell lines, organoids, tumor xenografts).

4) To provide human whole-cell/biopsy simulation supplemental data to reinforce animal model results for the IND.

By simulating drug impacts directly on human biopsy samples, ThinkingNode empowers its biopharma customers to provide stronger preclinical studies and accelerate the transition to clinical trials. In the future, we believe that human BioClone simulations will be systematic for any drug R&D.

ThinkingNode whole-cell-centric approach brings a transformative shift for drug R&D.