Drug Discovery. Faster.

Crystal Clear Vision

Our AI model reduces the number of missed protein crystals by over 30% compared to state-of-the-art benchmarks. Slash drug discovery costs without sacrificing quality.

Make Your Lab Work Smarter, Not Harder.

Crystal Clear Vision accelerates drug discovery by equipping laboratories with advanced AI-driven tools that reduce research time and costs. We can provide a personalized solution covering model training, fine-tuning, deployment, and customizable app/interface options to suit your needs.

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Maximize Data Capture with Precision AI:

Significantly reduce the number of missed crystals and achieve improved detection with training on as few as 60 new images.

40x Faster Processing, 30% More Crystals:

Achieve 30% fewer missed crystals compared to previous state-of-the-art models while using only 1/40th of the GPU power. This efficiency translates to substantial time savings—from 40 days to just one day.

Save Millions by Minimizing Missed Crystals:

Prevent bottlenecks in drug discovery and delivery. Minimize missed crystals in expensive membrane protein studies and potentially save your lab millions of dollars.

Customizable AI Exceeds Industry Benchmarks:

Our AI model not only meets but exceeds industry benchmarks. By fine-tuning the model, you can maximize operational efficiency and achieve exceptional results tailored to your specific research needs.

Why Crystal Clear Vision?

Our AI-powered model will outperform human-level performance and state-of-the-art benchmarks.

Expertise
in Computer Vision:

Appsilon's experts specialize in Computer Vision, implementing cutting-edge technology across top healthcare laboratories and Fortune 500 companies.

CCV adapts to any setting, bringing precision, and reducing costs.

Specialization in Drug Discovery Challenges:

CCV aligns with pharmaceutical giants, tackling protein crystal detection — a critical drug discovery efficiency bottleneck.

Our AI prowess is endorsed by leading pharma corporations, enhancing the drug discovery pathway.

See The Results

Explore the potential impact
of Crystal Clear Vision.

This calculator allows you to input parameters such as the number of conditions tested per attempt, the probability of crystal growth, and the expected number of attempts per month.

With this information, you can estimate the return on investment of integrating our machine learning model into your operations, in terms of both time and money.

The calculation of expected spotted crystals is based on the recall rates of each machine learning model (97% for CCV, 88% for MARCO, 77% for Human).
The 77% recall rate for humans is based on an agreement level on crystal identification from previous research. Using the user's input data and the recall rates for each model, we have calculated the time and number of attempts needed to obtain a high-quality crystal, and translated this into monetary terms, assuming each crystallization attempt costs approximately $15,000 USD.

For an easier assessment of the savings, we present comparisons between CCV and MARCO, and CCV and Human (manual inspection of all conditions).

Our process

Ready To Revolutionize Your Drug Discovery Process?

In the world of protein crystallography, the challenges faced by researchers are as diverse as the crystals they seek.

Every time you miss a protein crystal, you risk missing out on an important biomedical discovery.

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Get In Touch

Meet Appsilon's experts to gain comprehensive knowledge about our model and experience a live demonstration.

Send Us Your Imagery

Kickstart the collaboration by sending us a small sample of microscopic imagery featuring protein crystallization candidates.

Tailored Model Performance Report

Receive a comprehensive report detailing the performance of our solution, specifically tailored to your imagery. Understand how our model aligns with your unique requirements.

Potential Model Integration

Explore the possibility of integrating our model into your lab processes, offering an automated solution for the detection of protein crystals.

Whitepaper

AI in Drug Development: Fast and Accurate Protein Crystal Detection

Crystal Clear Vision technology reduces the need for extensive resources and expertise, making drug discovery more efficient. Learn more about AI's impact on protein crystallization and new medicines.

Who Benefits From Crystal Clear Vision

Unlocking Potential Across
Diverse Laboratories

01.

Big Pharma Laboratories

With insights gained from collaborations with industry leaders, CCV aligns seamlessly with the high-tech requirements of big pharma labs, ensuring a customized approach to protein crystal detection.

02.

Small Pharma Laboratories

Even small pharma labs, with the right infrastructure in place, can harness the power of Crystal Clear Vision through our user-friendly app. Schedule a discovery call today to experience a live demo of our app. in action

03.

Research Institutes

In the collaborative world of research institutes, CCV is a driving force for progress in protein crystal detection. Through partnerships with prestigious institutions, CCV plays a vital role in cutting-edge research endeavors.

Accelerate Your Drug Discovery Pathway

Connect with Crystal Clear Vision for unparalleled efficiency
in your lab’s workflow.

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CASE STUDY

Reducing drug development costs through AI protein crystal detection.

Global top 1% Applied Science Institution, improving drug discovery processes.

Business problem

The process of drug discovery is notoriously costly and time-consuming, with protein crystal identification being a critical step that traditionally requires substantial computational resources and expertise.

The existing state-of-the-art model, MARCO, while effective, misses almost 10% of crystals and demands extensive computational effort.

This inefficiency leads to missed opportunities in identifying potential drug candidates, directly impacting the speed and cost of bringing new medicines to market.

Solution

Appsilon introduced Crystal Clear Vision (CCV), an innovative machine learning model that leverages transfer learning and Low-Rank Adaptation (LoRA) for fine-tuning, significantly outperforming MARCO.

By focusing on enhancing crystal detection accuracy and applying state-of-the-art techniques, CCV dramatically lowers the missed crystal rate to 3.6% (reduction in lost crystals of 61%).

Thanks to this boost in efficiency, larger scale surveys are enabled, leading to a reduced time to discovering new drug candidates.

“Every time you miss a protein crystal, because they are so rare, you risk missing on an important biomedical discovery.”
Patrick Charbonneau
Duke University, Lead Researcher in MARCO initiative
About Appsilon

At Appsilon, We Transform Data Complexities Into Streamlined Solutions.

Appsilon excels in turning data complexity into simplicity, optimizing every stage of the Life Sciences data journey, from collection to insightful action.

Deep Learning and Shiny

Our deep learning and Shiny expertise are at the heart of our approach, ensuring advanced analytics meet user-friendly design.

Projects for Major Pharma Companies

We're a trusted partner for the pharma giants, with engagements in 5 of the top 10 industry leaders.

150+ Successfully Delivered Projects

Our 150+ successful projects are testaments to our role in propelling the life sciences forward.

Github Stars

With over 2,000 Github stars, our open-source contributions are making a significant impact.

Widely Utilized CRAN Resources

Our tools on CRAN boast over 300,000 downloads, reflecting our strong open-source commitment.

Academic Contributions

Our expertise is validated by three published peer-reviewed papers, with three more in progress.

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