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MOMO Biotech

MOMO Biotech has developed TMEmic, a next-generation in vitro model that accurately simulates the tumor microenvironment for solid tumors. This technology identifies the mechanisms of drug resistance in cancer, enabling the design of more effective drug modalities before clinical trials begin.

London, United KingdomFounded 20221300+ followers
Updated 4 months ago

Funding

$50K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

Drug development for solid tumors is hampered by the difficulty of accurately predicting drug efficacy in preclinical studies. Traditional in vitro models often fail to replicate the complexities of the tumor microenvironment (TME), leading to high failure rates in clinical trials. This results in wasted resources and delays in bringing effective cancer treatments to patients.

Solution

MOMO Biotech offers TMEmic, an advanced in vitro platform that simulates the solid tumor microenvironment to predict drug response. TMEmic combines proprietary biomaterials, integrated sensors, and a bioinformatics workflow to model the complex interactions within the TME. By recreating the barriers and resistance mechanisms tumors employ against drugs, TMEmic helps identify why some cancers resist treatment. This enables the design of more effective drug modalities and the selection of drug candidates with a higher likelihood of success in clinical trials.

Target Audience

MOMO Biotech's primary customers are pharmaceutical and biotechnology companies developing novel cancer therapeutics, as well as academic research institutions studying drug resistance mechanisms.

Features

  • Proprietary material formulations that mimic the physical and biochemical properties of the tumor microenvironment
  • Integrated sensors for real-time monitoring of key parameters within the TME
  • Comprehensive bioinformatics workflow for analyzing drug response and identifying resistance mechanisms
  • Ability to model the interactions between cancer cells, immune cells, and the extracellular matrix
  • Predictive power to identify drug candidates with a higher likelihood of success in clinical trials
This profile is AI-generated and may contain inaccuracies.