Netabolics | Predictive Biosimulation for Drug Discovery

We use digital human cells
to understand diseases

Our AI-driven biosimulation platform provides unprecedented decision analytics to de-risk drug discovery

THE COMPANY

Netabolics Predictive Biosimulation

Netabolics is an award-winning AI-driven biotech startup based in Rome, Italy. The company works to bring disruptive innovations in the pharmaceutical R&D processes. Our team includes life scientists and software engineers working collaboratively to produce the best and cost-effective computational tools for in silico drug target selection.

Our discovery platform predicts the biological changes occurring inside any cell type in response to pharmacological, genetic and environmental factors — in real-time. Predictions do not have to be perfect, but they need to inform decision-making in drug discovery, because quicker Go/No-Go decisions accelerate the progress towards safe and effective medicines for patients.

Mauro DiNuzzo, Founder & CEO

At Netabolics, we envision a future where drug discovery is transformed through the power of AI and biosimulation. Imagine a world where you can simply specify the desired outcome, such as a healthy cellular phenotype, and let our technology identify the most promising biological target, or combination thereof, for advancing your drug discovery pipeline.

Our mission is to accelerate the development of new medicines that make an impact on people.

We have an international network of academic, industrial, and technological partners, collaborating research laboratories, and customers that trust our technology.

We constantly seek mission-aligned partners to advance our discovery platform.

THE TECHNOLOGY

Where AI Meets Digital Twin

Our technology couples enzyme/receptor kinetics with branches of deep reinforcement learning overlaid onto first principles of physics and biology to automate networks/systems biology and pharmacology model simulations and empower drug discovery project teams to identify and validate the biological targets of diseases.

By leveraging artificial intelligence and publicly available databases, our proprietary algorithms create dynamical systems starting from digital reconstructions of human cells for predicting the effect of new drugs on cellular biology. From molecules to cellular homeostasis.

What is slowing down your R&D process in a typical use case scenario.

Your Data

You have multiomics (e.g., transcriptomics RNAseq) data from healthy and diseased cells.

Your Analysis Endpoint

You get a ranked list of differentially expressed genes/proteins and you can prioritize few of them for validation and further development.

Your Unmet Needs

You don’t know if each of those targets is disease-associated or disease-modifying (disease understanding).
You don’t know how diseased cells respond to perturbations of each of those targets (efficacy).
You don’t know how healthy cells respond to perturbations of each of those targets (toxicity).
You don’t know how many other targets relevant to disease with normal expression pattern you have missed!

What is our approach to in silico drug target selection using AI and biosimulation.

Outcome-Driven

We believe in simplifying the drug discovery process. Instead of navigating through complex pathways and countless potential biological targets, you can now focus on your desired outcome. Whether it’s targeting specific cellular functions or achieving a particular therapeutic effect, Netabolics empowers you to set the goal, and the platform will handle the rest.

Customized

Every project is unique, and so are your goals. Netabolics tailors its simulations to your specific requirements, ensuring a personalized approach to drug discovery. Whether you are a pharmaceutical company, research institution, or a biotech startup, our platform adapts to your needs, providing a customized solution for your projects.

Cutting-Edge

Our platform utilizes state-of-the-art biosimulation and AI/ML models to simulate and analyze biological networks. By leveraging advanced deep reinforcememt learning (DRL) algorithms, Netabolics identifies efficacy and toxicity biomarkers as well as the optimal biological targets that align with your defined outcome (e.g., as mono- or combination therapy). This accelerates the drug discovery process, saving you time and resources.

Here we show our predictive analytics on a model system of human erythrocyte (red blood cell).

Our proprietary biosimulation algorithms are rooted in biochemistry and are incorporated in a suite of powerful computational tools based on AI/ML that ensure full compliance with non-equilibrium thermodynamics across the entire modeling pipeline.

Mauro DiNuzzo. How artificial intelligence enables modeling and simulation of biological networks to accelerate drug discovery. Frontiers in Drug Discovery, Section In silico Methods and Artificial Intelligence for Drug Discovery, Volume 2 (2022). https://doi.org/10.3389/fddsv.2022.1019706

THE PLATFORM

Drug Target Selection in the Cloud

Our platform integrates the predictive power of AI/ML with the explainable and deterministic nature of ordinary differential equation (ODE)-based biosimulation. Applications include what-if scenario analysis to validate known biological targets, and target deconvolution analysis to discover novel biological targets.

We help identify and validate the biological targets of disease, predicts the biological effects of new drugs and optimize their efficacy and toxicity profile, which translates in substantial time and cost savings.

Not sure about our discovery platform? Don't trust us. Request a demo.

Ready to revolutionize your drug discovery pipeline? Contact Netabolics today to explore how our AI-powered simulations can propel your projects forward. Specify your desired outcome, and let the future of drug discovery unfold with us.

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Netabolics SRL
Circonvallazione Ostiense 229, 00154 Rome, Italy
VAT: IT-15768861005 | REA: RM-1612733

COOKIE POLICY PRIVACY POLICY TERMS OF USE

Netabolics received funding from the European Regional Development Fund Pre-Seed Regione Lazio POR-FESR 2014-2020. The aim of the Pre-Seed grant (Prot. n. A0122-2020-34411 - 10/03/2020) is to support the development of the proprietary cloud platform of the company (as academic spin-off) and the consolidation of the business idea to make it ready for the market.

We use digital human cellsto understand diseases

Our AI-driven biosimulation platform provides unprecedented decision analytics to de-risk drug discovery

THE COMPANY