Discover 5 Top Machine Learning Startups impacting Biopharma

Curious about new technological advancements in the pharma industry? Explore our analysis of 111 global biopharma startups & scaleups and learn how their machine learning solutions impact your business!

Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the pharma industry. This time, you get to discover five hand-picked machine learning startups impacting biopharma.

Out of 111, the Global Startup Heat Map highlights 5 Top Machine Learning Startups impacting Biopharma

The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering 2 093 000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.

The Global Startup Heat Map below reveals the distribution of the 111 exemplary startups & scaleups we analyzed for this research. Further, it highlights five biopharma startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these five startups & scaleups in this report. For insights on the other 106 machine learning solutions for biopharma, get in touch with us.

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Agxio accelerates Veterinary Drug Discovery

Founding Year: 2018
Location: Cambridge, UK
Funding: USD 900 000
Partner For: Parasitology

UK-based startup Agxio advances veterinary drug discovery. The startup combines machine learning and data analysis to accurately generate drug response prediction models and, in turn, identify strong leads. This also facilitates the use of targeted action on disease and drug efficacy. Besides, the startup’s AI-powered parasite classification solution minimizes errors and mitigates risks of anthelmintic resistance. Consequently, animal health companies are able to accelerate their drug development pipeline while reducing blanket treatments.

1910 Genetics offers Computational Drug Design

Founding Year: 2018
Location: Cambridge, US
Funding: USD 22 M
Partner For: Drug Lead Optimization

US-based startup 1910 Genetics develops computational drug design and discovery platforms. It uses ML to generate novel drug candidates while shortening the timeline and cutting operational costs. SUEDE, a hit discovery platform, captures compound desirability with validated pharmacophores. BAGEL, a hit-to-lead platform, enables the development of novel scaffolds from molecular templates using neural networks. The startup’s solutions find optimal drug formulation candidates.

Anagenex engineers DNA Encoded Libraries (DEL)

Founding Year: 2019
Location: San Francisco, US
Partner For: Rapid Drug Discovery

US-based startup Anagenex develops DNA encoded libraries. By combining ML with proprietary DELs, it analyzes more compounds and generates useful data to identify better compounds faster. The startup builds compound libraries and deploys custom selection methods. Analyzing the resulting data with ML and computational chemistry, it generates insights to design follow-up experiments. The process accelerates molecule development for medically important targets.

myNEO provides Personalised Immunotherapy

Founding Year: 2019
Location: Ghent, Belgium
Partner For: Neoantigen-driven Immunotherapy

Belgian startup myNEO engineers target discovery solutions for immunotherapy. The primary therapeutic focus of the startup is a patient-specific tumor screening platform. It provides personalized immunotherapy through neoantigen prediction. A validated set of tumor-specific surface molecules is chosen and validated per patient. The software module integrates experimental and clinical validation. The startup also uses big data analytics to identify alterations frequently shared among patients and to explore other inter-patient associations.

Thinkcyte facilitates Automated Cell Sorting

Founding Year: 2016
Location: Tokyo, Japan
Funding: USD 100 000
Partner for: Cell Type Prediction

Japanese startup Thinkcyte leverages machine learning (ML) for automated cell sorting. It characterizes and sorts cells at high-throughput rates by integrating a novel imaging technique. Image information of each cell is recorded as a waveform which the solution’s ML model analyzes to predict the cell type. Thinkcyte’s technology finds use in drug discovery, cell therapy development, and functional genomics.

Discover more Pharma Startups

Pharma startups such as the examples highlighted in this report focus on gene therapy, cell therapy, and therapeutic target discovery. While all of these technologies play a major role in advancing the pharma industry, they only represent the tip of the iceberg. To explore pharma technologies in more detail, simply let us look into your areas of interest. For a more general overview, download our free Pharma Innovation Report to save your time and improve strategic decision-making.

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