Precise compound screening with AI
AI-based recognition of diverse features of each single-cell allows for more precise phenotypic classification and quantification. An accurate capturing of drug responsiveness leads to more speedy discovery of truly effective compounds.
In addition, faster evaluation by AI enables mass screening in a short term period and strongly supports faster lead compound identification.
Support for diverse screening methods
s the difficulty of drug discovery increases, the methods used for compound screening are becoming more diverse. The speed and precision of evaluation achieved by AI analysis will contribute to faster compound screening.
Support measures examples
AI-based phenotypic screening
Supports screening of lead compounds by morphological changes of cells. By analyzing images of the phenotype of all cells at the single cell level, precise evaluation of drug response can be delivered.
Quantification of cellular response by drug concentration
Realization of automatic evaluation and quantification of drug responsiveness (nuclear translation of target proteins) of cells in response to drug concentration by image analysis.
Why you can rely on LPIXEL
By capturing features that cannot be captured by the human eye, it enables more precise morphological evaluation and quantification of cells.
Screening of a large number of compounds can be achieved in a short term period while significantly reducing the time required for evaluation.
AI can achieve higher reproducibility than human experimentation and observation.
More than 100 joint researches
Mainly in partneship with academia and research institutions in and outside of Japan, LPIXEL conducts
numerous joint researches with pharmaceutical companies.
Our seasoned and experienced specialists support you in implementating AI.
We offer free of charge services for hearing about issues and consulting for AI implementation, and evaluation analysis.
We look forward to working with you.
Hearing of issues
Data collection for analysis
How many images are required to build an AI?
In many cases, we would like to receive several tens to hundreds of images for the initial verification phase, and several hundreds to several thousands of images for the implementation phase.
How long does it take to build a AI?
Depending on the content and phase, we often take 3-6 months after receiving the data.
What is the difference between this product and existing analysis software or products from other companies?
AI engineers with abundant experience in life science experiments perform implementation, enabling implementation that meets the customer's needs. Unlike general-purpose software, our product is arranged for each customer's issues and researches.
Our team that consists of employees with a variety of experiences such as engaging in RA/QA of one of the largest medical device companies, and working for a medical system provider and a pharmaceutical company accelerate partners’ business together.
We provide optimal solutions by applying image analysis and artificial intelligence technologies in all life science fields such as medicine, pharmaceuticals, agriculture, chemistry, and food.