Wet Lab Testing of AI-Designed Drugs and Proteins
We are at the forefront of a transformative era in drug discovery and synthetic biology.
AI is revolutionizing the field by enabling the de novo design of drug molecules that specifically target, as well as optimizing the efficacies and safety profiles of lead drug molecules.
We are at the forefront of a transformative era in drug discovery and synthetic biology.
We are at the forefront of a transformative era in drug discovery and synthetic biology.
AI is revolutionizing the field by enabling the de novo design of drug molecules that specifically target, as well as optimizing the efficacies and safety profiles of lead drug molecules.
Objective wet-lab testing data to validate artificial intelligence (AI) designed drugs
Objective wet-lab testing data to validate artificial intelligence (AI) designed drugs
Our Platform
Validating in silico designed drugs
Accelerate Drug Development with SPOC
The SPOC platform is a powerful in vitro tool to rapidly evaluate in silico designed drug molecules, providing real-world data on drug-protein interactions. This facilitates multiple iterative design and testing cycles, crucial for developing drugs with optimal therapeutic effects.
The SPOC platform is a powerful in vitro tool to rapidly evaluate in silico designed drug molecules, providing real-world data on drug-protein interactions. This facilitates multiple iterative design and testing cycles, crucial for developing drugs with optimal therapeutic effects.
AI-Driven Drug Design
AI-Driven Drug Design
SPOC SPR & MALDI: generate data at scale to train AI models
We are in the early stages of AI-driven drug design. Current AI models are primarily trained on limited datasets of known drug-protein interactions, which restricts their predictive accuracy.
Given the vast and complex landscape of potential drug-target interactions, the effectiveness of these AI models is closely tied to the scale and quality of the training data.
The SPOC platform's kinetic screening capabilities provide deep characterization data using surface plasmon resonance (SPR) real-time biosensing, which is not achievable with current phage and yeast display technologies. SPOC enables large-scale, whole-proteome screening, generating tens of thousands of kinetic data points at a fraction of the cost compared to traditional recombinant protein SPR workflows.
Additionally, we are advancing our capabilities to enable N x M screening with SPOC using MALDI-TOF mass spectrometry profiling. This approach will generate millions of drug-protein interaction data points in a single run, complementing the SPR kinetic deep characterization data, and significantly enhancing the depth and breadth of AI model training datasets.
SPOC SPR & MALDI: generate data at scale to train AI models
We are in the early stages of AI-driven drug design. Current AI models are primarily trained on limited datasets of known drug-protein interactions, which restricts their predictive accuracy.
Given the vast and complex landscape of potential drug-target interactions, the effectiveness of these AI models is closely tied to the scale and quality of the training data.
The SPOC platform's kinetic screening capabilities provide deep characterization data using surface plasmon resonance (SPR) real-time biosensing, which is not achievable with current phage and yeast display technologies. SPOC enables large-scale, whole-proteome screening, generating tens of thousands of kinetic data points at a fraction of the cost compared to traditional recombinant protein SPR workflows.
Additionally, we are advancing our capabilities to enable N x M screening with SPOC using MALDI-TOF mass spectrometry profiling. This approach will generate millions of drug-protein interaction data points in a single run, complementing the SPR kinetic deep characterization data, and significantly enhancing the depth and breadth of AI model training datasets.
SPOC SPR & MALDI: generate data at scale to train AI models
Purpose-designed proteins represent the next frontier in biotechnology, whether inspired by natural proteins or designed entirely from scratch. Imagine novel proteins or enzymes engineered to more effectively capture carbon for climate change mitigation, accelerate the breakdown of plastics for faster biodegradation, catalyze the low-energy splitting of water to produce hydrogen for fuel cells, or synthesize key ingredients on demand for various industries, such as cosmetics. Innovators around the world are pioneering these exciting new approaches.
However, novel proteins produced through synthetic biology often face challenges such as poor expression or toxicity in cell-based systems. The SPOC platform addresses these issues with its cell-free production method, enabling the production and screening of virtually any novel protein design, a library of protein designs tested at once. It also supports downstream kinetic affinity screening with binding partners to quickly assess functionality. In the future, we plan to incorporate protein activity testing assays on the SPOC platform to further expand its capabilities.
SPOC SPR & MALDI: generate data at scale to train AI models
Purpose-designed proteins represent the next frontier in biotechnology, whether inspired by natural proteins or designed entirely from scratch. Imagine novel proteins or enzymes engineered to more effectively capture carbon for climate change mitigation, accelerate the breakdown of plastics for faster biodegradation, catalyze the low-energy splitting of water to produce hydrogen for fuel cells, or synthesize key ingredients on demand for various industries, such as cosmetics. Innovators around the world are pioneering these exciting new approaches.
However, novel proteins produced through synthetic biology often face challenges such as poor expression or toxicity in cell-based systems. The SPOC platform addresses these issues with its cell-free production method, enabling the production and screening of virtually any novel protein design, a library of protein designs tested at once. It also supports downstream kinetic affinity screening with binding partners to quickly assess functionality. In the future, we plan to incorporate protein activity testing assays on the SPOC platform to further expand its capabilities.
"Our AI models generate numerous drug candidates, a sub-set of which are synthesized and evaluated using in vitro assays. In vivo functional efficacy is correlated to a combination of both binding-epitope and kinetic affinity. There are no high throughput deep-characterization tools for epitope mapping and kinetics that can us help down-select, where data can further train our AI-models."
AI Drug Discovery Company
"Our AI models generate numerous drug candidates, a sub-set of which are synthesized and evaluated using in vitro assays. In vivo functional efficacy is correlated to a combination of both binding-epitope and kinetic affinity. There are no high throughput deep-characterization tools for epitope mapping and kinetics that can us help down-select, where data can further train our AI-models."
AI Drug Discovery Company
For more information on the SPOC platform, get in touch:
Information
Contact Us
1600 Adams Drive
Suite236
Menlo Park, CA 94025
7201 E Henkel Way
Suite 285
Scottsdale, AZ 85255
480-219-9506
info@spoc.bio
For more information on the SPOC platform, get in touch:
Information
Contact Us
Privacy & Conditions
1600 Adams Drive Suite236 Menlo Park, CA 94025
7201 E Henkel Way, Suite 285 Scottsdale, AZ 85255
480-219-9506
info@spoc.bio
All rights reserved © 2024
For more information on the SPOC platform, get in touch:
Information
Contact Us
Privacy & Conditions
1600 Adams Drive Suite236 Menlo Park, CA 94025
7201 E Henkel Way, Suite 285 Scottsdale, AZ 85255
480-219-9506
info@spoc.bio
All rights reserved © 2024