Drug Farm utilizes its IDInVivo⁺ platform, which employs piggyBac transposon mutagenesis for genetic screening in living animals, to identify novel drug targets for immunological diseases. By integrating this with the MedChem5 platform, which accelerates drug development through deep learning, Drug Farm advances first-in-class therapies for conditions such as hepatitis B and cancer.
Funding
$27M 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.
YCFounders
Product
Problem
The discovery of novel drug targets for immunological diseases is a complex and time-consuming process, often relying on traditional methods that lack the efficiency and precision needed to address unmet medical needs. Existing drug development approaches may not fully leverage the potential of genetic screening in living organisms with intact immune systems to identify effective therapeutic targets.
Solution
Drug Farm leverages its IDInVivo⁺ platform, which employs piggyBac transposon mutagenesis, to conduct genetic screening in living animals and identify novel drug targets for immunological diseases. This platform is integrated with the MedChem5 platform, which utilizes deep learning technologies to accelerate the development of first-in-class drugs. By combining these platforms, Drug Farm aims to streamline the drug discovery process, identify novel immunity targets, and advance drug candidates to clinical stages for conditions such as hepatitis B, hepatocellular cancer, cardio-renal disease, colitis, and Alzheimer's.
Target Audience
Drug Farm's primary target audience includes researchers and pharmaceutical companies focused on developing innovative treatments for infection and immunological diseases.
Features
- IDInVivo⁺ platform: Utilizes piggyBac transposon mutagenesis to generate a library of genetic mutations in mice for in vivo target discovery.
- In vivo genetic screening: Analyzes mice with mutated individual genes to identify drug targets connected to host immunity.
- In vitro validation: Validates potential drug targets using in vivo genetics and in vitro biochemistry and cell biology.
- MedChem5 platform: Employs deep learning technologies to accelerate drug development.
- Pipeline: Developing drug candidates for Hepatitis B (DF-006), Hepatocellular cancer (DF-006), Cardio-renal disease (DF-003), ROSAH syndrome (DF-003), Colitis (DF-004), Alzheimer's (DF-005), Cancer (DF-007), and Colitis (DF-X1).