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Complex Intelligence Technology (from BioStrand, a subsidiary of IPA)

LENSai™ Applications

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ENGINEERED for the AI Scientific Race

IPA integrates in silico

Overview

In silico, in parallel, in an instant.
Here's why.

By embedding The LENSai Complex Intelligence Technology from BioStrand (a subsidiary of IPA) into every step of the IPA antibody discovery process, we set a new standard for developing life-saving therapies faster, with more insight and more accuracy. The LENSai applications lend great cost and time efficiencies to our antibody discovery partners. Industry leading1, robust contract research (CRO) laboratory capabilities, combined with the most advanced in silico technologies, mean no need to invest elsewhere (i.e., for time- and cost-consuming assays, etc.)

Current applications

Here’s how.
LENSai Product Portfolio: In silico, in house

Retain diversity and eliminate redundancy. Make informed clinical lead candidate selections earlier and faster.

Immunogenicity Screening

Immunogenicity Screening

Our ultra-scalable immunogenicity screening algorithm gives rapid, unparalleled, and cost competitive rankings of your candidate antibodies.

Epitope Mapping

Epitope Mapping

We provide early-stage triaging of large antibody panels by providing detailed in silico epitope footprints.

Clinical OT

Clinical Off-Target Analysis

High throughput assessment and profiling with efficient identification of candidates for clinical success…

 
See how it works

Contact our LENSai portfolio expert to walk-through customized applications for your project.

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IPA AI Cost Efficiency
Making data manageable and meaningful
The problem we’re solving

Artificial intelligence is missing the target for antibody discovery in the life sciences. Here’s why.

While multi-omics data science enables great opportunity with access to massive amounts of new biological data, the sheer volume of information poses inherent challenges for making it manageable and useful, for antibody discovery. The capability for AI to bridge the gap between wet lab limitations and in silico efficiencies has fallen short for biotherapeutic research and analytics.

The challenge

The paradox of too much data
(for pharmaceutical companies)

  • sequencing capabilities far outpace the ability to decipher the resulting data
  • our ability to analyze and use the data has been limited with existing tools and real or artificial intelligence
  • the gap is widening

No way to analyze it against existing
healthcare data, efficiently

  • biological data is unstructured, including text data from scientific literature and other clinical information sources
  • classifying, labelling, indexing, and storing biological datasets too confined by discretionary frameworks, with variables and parameters
  • this approach inherently restricts the ability to match data sets that may exist far outside of the parameters of what is known, and not known

A whole new approach to A.I.

The solution

LENSai Complex Intelligence Technology

IPA has made a mission of finding the next-gen intelligence to solve the paradox and render the data useful for its pharmaceutical customers— and the patients they serve. LENSai introduces a whole new approach to AI technology for antibody discovery with the ability to:

  • code and index data using universal biological fingerprints as primary tools (in the software)
  • remove unnecessary searches or irrelevant sequences and structures
  • analyze data from multiple domains and dimensions — concurrently
  • make complex data specific and applicable — instantly
  • perform rapid exploration, interrogation, and correlation of new and existing data or omics

IPA LENSai

 

Uniquely equipped to reduce risk, time and cost for antibody discovery

IPA AI HYFTs

HYFTs® organize the biosphere with Universal Fingerprints™

  • carry layers of info and metadata that can be continuously added
  • multi-layers of function, structure, positions etc. that form a multi- level intelligence network
  • crystallizes specificity

 

IPA ai 3D

Concurrent analytics in 3D of text, sequence, and protein structure

  • combines and analyzes data in the three key dimensions of text (literature), sequence and protein structure simultaneously
  • interrogates and decodes structured and unstructured datasets (i.e., biological, literature, public and private domains, all recorded sequence data from the biosphere)
IPA AI mass data

Making mass data meaningful

  • the only technology with an embedded sequence /structure function view
  • next-gen intelligence to render the data useful for drug discovery

The next evolution for CROs and the new definition of end-to-end service.

The next evolution for CROs and the new definition of end-to-end service.

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