AI Generation Era

AI generation era has come, this change will also shake the biomedical field, traditionally biomedical also need to use AI, but AI only play an auxiliary role, now generative AI will bring more opportunities for the biomedical field.

Generative AI in Biopharm

Only AI can help us program complex living systems. Living systems are so complex that we cannot find a set of principles to program life precisely. But AI can solve this problem by discovering these implicit associations from. Meanwhile great progress has been made in the field of multimodality. And based on the fact that natural language programming is extremely accessible, it is now beginning to change the future of life sciences as well.

Hidden Patterns

1. The complex patterns in life are difficult to summarise and generalise, requiring generative AI for application.
2. Generative AI can directly apply hidden patterns that are difficult to illustrate.

Multi-modal Optimal

1. Reject the risk of one-way “trial and error” search falling into local optimal solutions.
2. AI considers multi-modal constraints and generates global optimal solutions.

User Friendly

1. Easy to learn and more user-friendly for biologists than previous generations of AI.
2. Transfer learning can be performed, making it easier to extend to multiple scenarios.

Proteins Match with Language Models

Proteins as the core language of the life sciences are naturally adapted to big models, and protein language corresponds to natural language in several structures. Once biologists have fully cracked the code of the protein universe, proteins with new, specialized functions can be generated with the assistance of generative AI. This will be a milestone in the field of synthetic biology and will revolutionize the history of the life sciences themselves.

Primary

Amino Acids

QVQLQESGPGLVRPSQTLSLTCT
VSGFTFTDFYMNWVR…

Alphabets

ABCDEFGHIJKLMNOPQRSTV
UWXYZ…

Secondary

Domains

Words

Bob
Ride
Bicycles

Tertiary

Structure

Sentence

Bob rides the bicycles.

Quaternary

Interaction

Paragraph

Bob rides the bicycles to school. While the traffic is always busy…

BayVax: Protein Language in Immunity

But one big model can’t solve all the problems, the key lies in the model tuning in the segmentation field. Specifically, we apply the protein language of life sciences to immune discrimination, and we have built an exclusive immune design platform by simulating the classifiers of the human immune system itself, which gradually realizes immune system programming.

Human Immune System Discriminator

Bayesian Simulated Immune Discriminator

BayVax: Generator + Discriminator

We focus on immunogenicity prediction and immune-related model tuning and molecule generation. Currently our team has implemented a platform for generator+discriminator tandem generation of antigens and drugs.

Protein Generator

Immunity Discriminator

Molecule

BayVax Has Generated Cancer Vaccines

In addition, BayVax has achieved efficient generation of vaccines, which can be generated from a wide range of potential sequences for a particular antigenic epitope, and experimentally validated to stimulate an immune response.

AI Generation

Experiment Validation

AI-generated Drugs (AIGD)

Not only AIGC, we will use AI to be able to generate drugs, the AIGD market is huge, we are talking about gradually expanding from the $10 billion antigen design, to a broader market, and ultimately immune programming.

Immune Programme

(Ultimate)

Drug Design

($ 1000B)

Antibody Design

($ 200B)

Antigen Design

($ 10B)

How to Programme Immune System?

IMMUADJ - Novel Vaccine Adjuvant

A new formulation is safer, more effective, and more convenient.

Peptide drug conjugates improve water solubility, immunogenicity, and safety

Stronger Immune Response

Better Therapeutic Efficacy

Antigenicity Prediction Model

BayVax can effectively predict immune escape of new variants for the future.

Founder / Advisor Board

This change spans multiple fields and will be a convergence of immunology, informatics, and commercialization, and our team includes experts in all of these fields; I have a PhD in medicine that crossed over from computers to immunology, and the team also includes drug reviewers, and our advisors include a number of industry leaders.

Founder

Jian-Dong HUANG

Professor

CSO

Chair Prof. of Synthetic Biology, HKU

Ye-Fan HU

PhD

CEO

Computational Immunologist/ iGEM Gold Medal

Robert JIANG

PhD DABT

IND Expert

External review expert of NMPA-CDE

May CHEN

MPH

COO

Senior medical practitioners

Served dozens of new drug launch and marketing

Advisor Board

Thoma YAU

Clinical Associate Professor

Immunologist

Clinical Associate Prof. of Medicine, HKU

Yigang TONG

Professor

Bioinformatician

Dean, BUCT

Xiaodan FAN

Professor

Deep-learning Experts

Professor, Dept. Statistics, CUHK

Our vaccine patent is awarded with Gold Medal of Geneva Invention.

We are funded by HKSTP IncuBio Programme with up to 6M HKD equity-free support.

We have fundraised ~5M HKD seed funding from Miracle Plus (former YC China) and another private investor.