We are the world’s first systems medicine platform for advanced complex therapies, paving the way to develop true synthetic biology based therapeutics to cure the most complex diseases.

Approach

Complex biological modelling leveraging the intersection of mechanistic and AI-based hybrid modelling methodologies.

Platform

Mechanistic, quantitative models on a molecular level that are able to explore design spaces of complex products in-silico to inform design decisions

Pipeline

Our pipelines leverage the most advanced high throughput experimental technologies to inform our models.

We're overcoming significant challenges that will have a great impact for patients.

90%

of clinical trials fail, even though each therapy can take 10-15 years and up to $1Bn to get to market.

$28b

per year worth of experimental resource wastage in the USA per year on irreproducible research.

3726

cell and gene therapies currently in development with an annual growth rate of 7%

$2b+

being invested into new cell and gene therapy startup companies every year

We've designed a pipeline that tackles the complexity of otherwise incomprehensible systems by leveraging first principles modelling techniques in combination with cutting edge active and deep learning.

Our models are complex dynamical systems, composed of multiple subsystems of interacting cell types. These models are tied to quantitative data via hybrid AI, which allows us to estimate where critical transitions in these dynamical systems happen, and how they are impacted by patient biomarkers and multi-modal therapies

Tumour Micro-Environment (TME)

Status: Prototype Development

Our models guide critical decisions in early development to unlock predictions about the efficacy and safety of potential therapeutics. Our model minimises risk and maximises outcome based on rational integration of all currently available data.

TME - Product Model

Status: Prototype Development

We are building a comprehensive library of models for major nanoparticle technologies that can be adapted to specific client products, including: Oncolytic Viruses, Viral Vectors, LNP/VLP for use alongside our TME model.

We help to identify the optimal next experiments to maximise information gain by leveraging our biophysical modelling pipeline.

This pipeline is designed around active learning paradigms that based on data input, gives our model the ability to estimate the position of the system in state space (key characteristics of the system).

We integrate quantitative data from in vitro reconstitution assays such as:

  • Tumour-on-a-chip
  • Microfluidics
  • Organoids
  • Single cell assays

    How will it work for you?

    Before proceeding to clinical trial, we computationally simulate the efficacy of the therapy on impacting tumour microenvironment behaviour to understand the complex mechanisms driving the therapeutic effects. Evaluating these in-silico experiments allows our customers to gain insight into which therapies or combination of therapies can potentially lead to patient benefit.

    STEP 1

    Product + pipeline analysis

    We conduct a review of the products that our customers would like to test the efficacy for against our simulated TME. We also review their experimental pipeline to see whether additional data would improve results.

    STEP 2

    Data sharing

    Once this data is shared with us, we create specific Product models representing the product that the customers has shared with us. This product model remains the IP of the customer.

    STEP 3

    Simulation Results

    We will produce results of running the product(s) against our TME and provide results of the efficacy, safety and any further advice regarding how they may be able to improve the therapy from co-targeting or arming.

    Our team.

    We’re here to augment the status quo in order to improve treatments for patients across the world. We understand that solving complex challenges and breaking boundaries is only possible with the right people. That is why we are people-centric.

    Rohit Makol

    Chief executive officer

    Experienced founder and product expert, CPO at Cardeo (FinTech), Ex-COO at HeyHub, Ex-Head of Product at CompareTheMarket.

    Jacob Halatek

    Chief technology officer

    Ex-Microsoft Research, Group lead of Biological Modelling at Oxford Biomedica. PhD in Theoretical Physics (LMU Munich)

    Luke Robinson

    Chief scientific officer

    Director at Post Urban Ventures, Chief Scientist at Hazy and FLOX, NED at Earth Rover, PhD in Physics (University of Cambridge)

    Siddharth Deshpande

    Data Science Advisor

    Ex-Evaluate NLP Data Scientist, Deep-tech scientist at Post UrbanVentures, PhD Medicine (National University of Singapore)

    We partner with organisations and academic institutions on projects that align with our development roadmap.

    Immunotherapy

    We work with companies that are developing immunotherapies and are looking to improve outcomes by leveraging the data they possess alongside our TME models.

    CONTACT US

    Tumour-on-a-chip

    Partnering with tumour-on-a-chip organisations allows us to share knowledge and information integral for the development of our shared and independent pipelines.

    CONTACT US

    Tumour Organoids

    Sharing a systems medicine based view of the TME with developers, allows for effective and efficient knowledge transfer.

    CONTACT US

    Join us in pushing forward synthetic biology.

    We're taking on new challenges in a truly multi-disciplinary arena to push the frontier of synthetic biology forward. This requires subject matter experts from biology, physics, mathematics, software and data science to come together to forward our mission in order to achieve our vision.

    We're location agnostic - Our team combines people from across the world.

    Join us on our mission

    We are a Post Urban Ventures company.

    I want to get in touch with you, how I can do that?
    FAQ ICON

    We're always happy to have a coffee. You can contact us on hello@bioleap.ai and someone will get back to you in due course. We're based across the UK but are primarily based in Cambridge, London and Oxford.