Internship
BigHat Biosciences
51-200 employees
Develops antibody therapies using machine learning
No salary listed
San Mateo, CA, USA
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- PhD in progress, BS/MS degree in ML, CS or in the sciences with significant ML experience and a strong mathematical background
- Strong competency in Python
- Familiarity with PyTorch
- Strong communication skills
- Sufficient biomedical domain knowledge to interact effectively with diverse scientific teams
- Develop and evaluate a novel ML modeling or sequence optimization approach to solve an antibody engineering challenge relevant to BigHat’s therapeutics programs
- Work with an interdisciplinary team of biologists, data scientists and machine learning scientists to gain sufficient domain familiarity to ensure your work is impactful
- Document and present your results to relevant BigHat departments
- Write production-grade code such that successful methods can be deployed and evaluated in the wet lab
- Experience with protein structure modeling
- Familiarity with antibody biology
- Experience training and deploying models on AWS
BigHat Biosciences focuses on developing antibody therapies using machine learning and synthetic biology. Their main product is the Milliner platform, which integrates a wet lab with advanced machine learning to rapidly design and engineer antibodies. This platform enables the synthesis, purification, and characterization of hundreds of antibodies each week, allowing for quicker development of treatments for challenging diseases like infections and cancers. Unlike many competitors, BigHat emphasizes a family-friendly work culture while maintaining high performance. The company's goal is to create safer and more effective therapies for patients, particularly those with difficult-to-treat conditions.
Company Size
51-200
Company Stage
Series B
Total Funding
$99.3M
Headquarters
San Carlos, California
Founded
2019
Simplify's Take
What believers are saying
- AI-driven protein engineering is crucial for personalized medicine and effective treatments.
- Collaborations with Synaffix and Merck highlight BigHat's strategic growth in ADCs.
- The biotech industry shift towards scalable biologics production benefits BigHat's efficient methods.
What critics are saying
- CEO transition may disrupt strategic direction and operations at BigHat.
- Dependency on Synaffix's ADC technology could pose risks if challenges arise.
- Rapid team expansion might strain resources and impact company culture.
What makes BigHat Biosciences unique
- BigHat's Milliner platform integrates AI with synthetic biology for rapid antibody development.
- The company focuses on difficult-to-treat diseases, offering unique therapeutic solutions.
- BigHat's partnerships with Janssen and Merck enhance its drug discovery capabilities.
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Benefits
Professional Development Budget
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 3%2 year growth
↑ 5%Co-founder Mark DePristo has stepped down as CEO of Bighat Biosciences Inc. and is succeeded by fellow co-founder Peyton Greenside, who was president and CSO.
The Danish company Adcendo and Chinese company Multitude Therapeutics entered into a $1 billion deal to develop ADCs for the treatment of cancer; and in August, the FDA lifted a partial hold on a Phase 1 trial evaluating an ADC candidate developed by MediLink Therapeutics and BioNTech for the treatment of advanced or metastatic non-small cell lung cancer and breast cancer.
BigHat obtains access to Synaffix's site-specific ADC technology platform, and plans to combine Synaffix technology with its advanced ML antibody design platform to develop a new ADC pipeline
Similarly, AbbVie is collaborating with BigHat Biosciences to develop next-generation antibody therapeutics using the Milliner platform, focusing on oncology and neuroscience.
SAN MATEO, Calif.--(BUSINESS WIRE)--BigHat Biosciences, a biotechnology company with an artificial intelligence/machine learning-guided antibody discovery and development platform announced a collaboration with Janssen Biotech Inc., a Johnson Johnson company. This strategic collaboration combines the drug discovery, clinical development and data science expertise from Johnson Johnson with BigHat’s Milliner™ platform, a suite of machine learning technologies integrated with a high-speed wet lab, to guide the design and selection for high-quality antibodies for multiple Neuroscience therapeutic targets. The agreement was facilitated by Johnson Johnson Innovation. BigHat’s antibody design platform, Milliner™, integrates a synthetic biology-based high-speed wet lab with state-of-the-art machine learning technologies into a full-stack antibody discovery and engineering platform, to engineer antibodies with more complex functions and better biophysical properties. This approach reduces the difficulty of designing antibodies and other therapeutic proteins to tackle conditions ranging from chronic illness to life-threatening disease, while also massively speeding up candidate discovery and validation. "We’re delighted to be collaborating with Johnson Johnson to utilize BigHat’s Milliner™ platform to accelerate protein design," stated Mark DePristo, CEO and Co-founder of BigHat