Digital Biology solutions that work
I help biotech companies improve design-build-test-learn efficiency and extract insights from mulit-omics data using my digital biology toolbox built on mature and emerging AI techniques.
How exactly can digital biology help?
Can digital biology help me?
Three questions for you, to help you assess:

Can you prove your experiments are the most efficient?
The challenge
If you're not designing experiments optimally, you're wasting a percentage of your resources with every experiment.
Every experiment should balance these two goals:

Improve your ability to predictably increase performance

Maximize the probability of improving performance with fewer experiments
What you from me:
  • Active learning and optimal experiment design produce provably efficient experiments
  • Reach higher performance with fewer experiments (I've see up to 3-4 times fewer experiments)
  • Improve predictability using 30-40% fewer experiment iterations

Can you predict what your strain will do before your bioreactor run?
The challenge
High-throughput strain design and screening isn't an economical option for many early-stage startups.
Here's a more accessible way:

Leverage simulation, your strain-specific knowledge, and genomics to perform high-throughput in silico (simulated) screens for a fraction of the cost.
What you get from me:
After a detailed assessment,
  • Working predictive simulator of your strain, product (non-native or native protein or metabolite) for your culture conditions
  • List and roadmap of the data, experiments, computing resources you need to make simulation a regular force-multiplier in your day-to-day

Do you know if you've learned everything you can from your multi-omic data?
The challenge
Transcriptomics, proteomics, metabolomics, fluxomics aren't trivial to analyze.
Integrating multiple omic data is even harder.
To discover new levers, you need

Unified model that integrates transcriptomics, proteomics, metabolomics, fluxomics, and fermentation data

Reliable system to extract fresh insights across multiple data sets
What you get from me:
  • I'll feed all your omic and fermentation data using the ideal tools
  • My toolkit includes state of the art, multi-scale unified simulators; robust machine learning and generative AI that leverage network knowledge
What our Clients are Saying

Christopher Long - Head of Systems Biology, Ginkgo Bioworks

In the course of an internal R&D effort to explore the use of next generation multi-scale cellular models, we engaged Philancea's consulting services. Despite our team's deep expertise in the space, we were hitting technical challenges in adapting complex, early stage (academic) code to our production environment. Dr. Yang brought critical expertise and bandwidth to solve these challenges, resulting in a satisfactory project outcome. Dr. Yang's systematic investigation revealed fundamental numerical instability issues that were causing inconsistent results across varying simulation conditions. The breakthrough came when they not only pinpointed the root cause of our simulation inconsistencies but also developed a proof-of-concept whole-cell model to validate their hypothesis. Their reformulated prototype demonstrated identical predictive capabilities while eliminating the numerical instabilities that had been plaguing our workflows, particularly when simulating varying feedstock uptake rates. This concrete evidence helped us understand exactly why our previous approach was struggling and provided a clear technical pathway forward. Based on this experience, I highly recommend Philancea's consulting services for organizations facing complex biological modeling challenges. Their ability to quickly diagnose deep technical issues and provide validated solutions, coupled with their practical, rapid prototyping approach and agile service model, has enabled us to make whole-cell modeling a reliable part of our workflow.

Jonathan Ho - Founder & CEO, Allium Bio

Working with Laurence as an Advisor has been a true partnership experience. From day one, he prioritized understanding our unique challenges at Allium Bio and tailored his insights specifically for our co-culture fermentation needs. His commitment to our success went beyond just helping us implement cutting-edge AI and simulation - he found innovative ways to strengthen our core capabilities, enabling us to explore 200 million strain-process combinations and promising strategies to achieve up to 5.2X yield improvements. His dedication to putting our objectives first has made him an invaluable partner in our mission to deliver safe, sustainable, and scalable ingredients for next-generation food products. Choosing to work with the Philancea modeling team was one of the best decisions we could have made during our early stage research. They have been an incredible resource and partner throughout the entire project. They also always went the extra mile, whether it was taking calls at odd hours of the night or pushing through specific model revisions just before a big presentation. Could not recommend them more highly! 10/10!

Katherine Decker - Computational Biologist, ProdermIQ

In our fast-paced startup environment, we were looking for ways to improve the efficiency and effectiveness of our internal computational pipelines, and working with Laurence provided exactly the expertise we needed. I learned a tremendous amount about advanced modeling techniques and how to effectively validate our pipeline. Watching Laurence's approach to problem-solving, such as developing custom algorithms to explore optimal parameters in bioinformatics and machine learning pipelines, has significantly improved my own analytical skills.His expertise in genome-scale modeling and machine learning helped us generate critical validation results that we can now confidently present to our clients. His insights have not only strengthened our current projects but have also built our in-house capabilities for future advancements. This collaboration has truly elevated our team's performance and the robustness of our prediction engine.

Sanjeev Dahal - Senior Computational Biologist, ProdermIQ

Laurence's impact on our company was astounding. His vast and deep expertise in genome-scale modeling and optimization algorithms proved invaluable. His coaching significantly accelerated our milestone achievements and key improvements to our computational platform. Using real-time sketching, he clarified complex concepts, while his detailed explanations ensured we grasped every modeling choice. Drawing from both industry and academic experience, Laurence offered innovative solutions we'd never even considered. His guidance has dramatically enhanced our modeling capabilities and problem-solving approach. Finally, his assistance enhanced our capability to communicate highly complex concepts and approaches to our clients.

Want to hit fermentation milestones reliably, using resources in the most efficient way possible?
Hitting yield and titer, and media optimization milestones across different reactor scales isn't a new problem. But it's still not straightforward. Your bottlenecks are unique:
  • unique product made by your chosen strain — is that the optimal pairing?
  • many possible bottlenecks to yield and titer: transcription, translation, post-translational modification, protein homeostasis, secretion, metabolism, stress response, mass transfer
  • optimizing your platform to work with a different product across customer projects — how to ensure your platform is getting more predictive, reliable, and consistent with every project?