Solutions

De Novo Discovery

How AI helps drug developers in the context of de novo discovery.

Introduction

De novo drug design (DNDD) uses a computational approach to allow researchers to design proprietary chemical entities, compounds, and drug candidates more quickly and economically than other drug design methods. While conventional DNDD methodologies use only the information regarding a biological target and its known active binders, recent advances in de novo discovery are leveraging quantum mechanical calculations as well as machine learning (ML), deep learning (DL), and other related AI-based technologies to explore the broadest chemical spaces possible – utilizing both state of the art computational chemistry methods and vast data troves from available scientific literature and databases. So while standard de novo design methods can be limited by existing knowledge around receptor–ligand interactions, breakthrough deep learning methods combine advancements in computational chemistry and artificial neural networks with reinforcement learning in order to discover novel drug candidates that are virtually “template-free.”

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Situation

By leveraging computational modeling, virtual screening and AI algorithms, de novo discovery is pushing the boundaries of traditional drug development approaches, potentially revolutionizing the early stages of the drug design and development process. Still, challenges remain.

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The VeriSIM Life advantage

VeriSIM Life (VSL)’s drug decision engine, BIOiSIM®, is making it easier to address both the synthetic accessibility of de novo generated compounds and any related black box transparency concerns head on. 

Using its groundbreaking Translational Index™️ technology, BIOiSIM® constrains everything by its translatability, rating drug candidates in order to deliver truly feasible de novo molecules. The Translational Index™️ also allows VSL to show our work, aiding regulatory and community acceptance, reducing AI-based skepticism, and ultimately establishing well-balanced profiles for candidate drugs. In this way, BIOiSIM™’s Translational Index™ helps avoid the pursuit of dead end candidates, advancing only the most promising drug candidates through R&D to investigational new drug (IND) application.

BIOiSIM®, and its groundbreaking Translational Index™️ technology

Which advances only the most promising drug candidates through R&D to investigational new drug (IND) application, offers actionable insights of unprecedented value to the drug development industry.

Combining thousands of validation data sets, multi-compartmental models, and its integrated AI/ML engine, BIOiSIM® achieves superior physiological and biological relevance within three classes of therapeutics: small molecules, large molecules, and re-engineered viruses.

The BIOiSIM® platform features a
robust data lake foundation, integrating:

1 trillion potential compounds search space for de novo synthesis and structural screening

1 trillion potential compounds search space for de novo synthesis and structural screening

Physiological data from 7 different animal species, plus humans

Physiological data from 7 different animal species, plus humans

Support for genomics data integration

Support for genomics data integration

More than 3,000,000 real compounds including proprietary data from multiple partnerships

More than 3,000,000 real compounds including proprietary data from multiple partnerships

Proprietary experimental data from scientific literature and other sources

Proprietary experimental data from scientific literature and other sources

Validation by real-world observed data

Validation by real-world observed data

Proof of Value

Translation-informed De Novo Discovery

Challenge

Challenge

VeriSIM Life’s partner needed a novel compound ready for synthesis and validation studies in weeks, but conventional drug discovery typically takes from between 5 to 36 months.

Solution

Solution

Using its Translational Index™️ technology, the BIOiSIM® platform enabled compound mapping and selection in order to identify the highest potential translatable compounds.

Methods

Methods

  • De novo synthesizer enabled target screening, structure validation, drug-like properties, viability and synthesizability.
  • BIOiSIM® generated novel Tyrosine Kinase inhibitor compounds based on 5 big-brand marketed structures.
  • Synthesized compounds were optimized in discovery based on superior bioavailability at lower dosing.
Outcome

Outcome

In only one month of discovery and pre-validation, VeriSIM Life generated three novel, high-potential candidates, representing a 50% reduction in overall development time. Leveraging the de novo synthesizer also resulted in more streamlined translational research. 

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“The BIOiSIM platform gave us a novel compound ready for synthesis and validation studies in just weeks versus the months or even years typical of conventional methods.”

Biotech client
Case studies

Additional VeriSIM Life Case Studies & Content

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How to Evolve from Traditional Model-Informed Drug Discovery & Development to an AI-Informed Approach

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BIOiSIM™ Drug Decision Engine: Breakthrough Intelligence to De-risk R&D Translation, Without Disruption

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Evolve your pipeline

Bring better drugs to market, faster, with BIOiSIM®

Now you can accelerate the discovery of new therapies based on existing compounds with VeriSIM Life’s BIOiSIM® computational platform – purpose-built to decode chemistry and biology at scale. With the industry’s most generalistic AI platform, your innovation is no longer limited to experimental constraints.

Contact us today to schedule a demonstration of BIOiSIM®