Validate. Replicate. Verify.PhilosophyTeamProduct

WELCOME TO BIOCOLLATE

Empowering the

next generation

of synthetic biology

Our Mission


According to a landmark study conducted in 2014, over 50% of scientists cannot reproduce their own work, and over 70% cannot reproduce the findings of their peers. This is a huge deal and calls into question the integrity of scientific progress!

At BioCollate, we are addressing the replication crisis by providing a platform for researchers to create protocols, collect data, organize results, and share scientific findings in a machine-accessible way conducive to repeating experiments from lab to lab.

By promoting the repetition of experiments and facilitating the entire Design-Build-Test-Learn (DBTL) cycle, we aim to enhance the reproducibility and reliability of scientific research.

We are dedicated to fostering a collaborative scientific community where data integrity and accessibility drive progress and breakthroughs.

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Collaboration

We're creating a powerful tool for scientists to collaborate and share data on, allowing for sound science and new discoveries.

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Data Integrity

We prioritize user data ownership and ensure integrity by tracking the timestamps and sources of all data points.

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Accessibility

With our emphasis on creating an intuitive user experience, our software will be accessible to scientists of any level of expertise.

BioCollate's Scientific Philosophy

We believe that all experimentation should be reproducible and replicable to follow the pillars of science.

Pillar

Repeatable Observations

A scientific hypothesis is judged by its alignment with consistently observed data both in nature and experiments.

Pillar

Elegant Hypotheses

A hypothesis should be elegantly crafted to be clear, intuitive, and straightforward, effectively conveying its purpose.

Pillar

Approximate Models

No model can capture all of reality, so we use overlapping theories for unique phenomena, with newer theories expanding on older ones.

Pillar

Precise Descriptions

A scientific hypothesis must be precisely stated to allow definitive testing, ensuring clarity for future work and avoiding ambiguity.

Pillar

Ethical Integrity

Science is driven by the pursuit of truth, requiring honesty, objectivity, humility, and the abandonment of political and personal bias.

Pillar

Community Examination

We are a truth-seeking community reliant on collaboration andreview to drive progress, ensuring that errors are corrected over time.

These Pillars of Science described by Dr. Aron Wall capture the fundamental ideas behind the scientific method and community that have been respected, unknowingly or not, for centuries. Here at BioCollate, we want to empower you, the researcher, to follow these pillars and create elegant, repeatable, community-driven science with our software.

Meet the Team

Our team combines extensive experience in synthetic biology, computational biology, and software development, uniquely positioning us to solve the challenges researchers face.

Sai Headshot
CEO: Sai SamineniPh.D. Biomedical Engineering
Emailsai@biocollate.com Sai, an expert in commercialization, developed the T-Detect COVID-19 test with Microsoft and Adaptive Biotechnologies. With a decade of synthetic biology experience and entrepreneurial skills from founding a tax and grant writing service, she adds immense value to the team.
Tom Headshot
COO: Tom StoughtonB.S. Computer Science
Emailtom@biocollate.com Tom brings expertise from his software engineering experience, developing products for full life-cycles. He has built applications from scratch, has background in computational biology, and his entrepreneurial Capstone experience equips him to drive innovation at BioCollate.

Introducing: Benchtop Lab Assistant

This service will be an all-encompassing platform for scientists to use through the entire DBTL cycle. We're focusing on the field of synthetic biology right now, but we see a need for this product in most fields of science.


The process starts with designing an experiment following the pillars of science. We'll help with that, providing feedback and suggestions using machine learning based on an outline.


Then, researchers take their outline and create a protocol using our intuitive workspace. BLA will keep track of variables, amounts, tools, machines, and everything else that needs to be recorded.


Once a highly-detailed machine-accessible protocol is made, the researcher can run the steps of their experiment with their automated lab equipment over a wireless connection. Then, like magic, BLA will automatically record data from the machines and save it for later analysis.


When the experiment is finished, the scientist can use our tools to analyze the data and draw a conclusion leading to new knowledge in the domain.

Diagram showing steps for user workflow. Design experiment leads to build machine-accessible protocols which leads to test on automated lab equipment. This leads to record data which points to both share protocols and results and learn from results. Learn from results points back to design experiment.

Developing 5-star software takes time, though, so we expect to have a prototype ready in the next two years. Stay tuned for more updates on the progress!