Author: adminds

In July 2025, PEACCEL presented new results at ICML 2025 in Vancouver, including two research contributions and two posters at the GenBio Workshop (Generative AI for Biology), a venue focused on the next generation of generative methods for proteins, RNAs, and small-molecule design.

What we presented

1) Diffusion Models with Group Symmetries for Biomolecule Generation
We explore how group symmetries can be built into diffusion models to better reflect the underlying structure of biomolecules, an important lever for improving sample efficiency, validity, and controllability in generative design.

Link: https://icml.cc/virtual/2025/51284

2) Benchmark of Diffusion and Flow-Matching Models for Unconditional Protein Structure Design
We provide a practical benchmark comparing diffusion and flow-matching approaches for unconditional protein structure generation, with an emphasis on decision-relevant tradeoffs for real-world R&D: robustness, design quality, diversity/novelty, and operational efficiency.

Link: https://icml.cc/virtual/2025/51228

Plus: Two posters accepted at the ICML 2025 GenBio Workshop, highlighting additional
results and perspectives on generative AI for biology.

Why this matters for drug discovery and drug design

Generative AI is increasingly central to biologics and protein engineering because it can:

• Compress design cycles by generating plausible structural candidates earlier and at scale
• Improve exploration of sequence–structure space beyond incremental local search
• Provide more rigorous, comparable evidence when selecting model families (diffusion vs flow-matching) and determining where to invest engineering effort

Our focus is to make generative modeling more physically grounded (via symmetry-aware
methods) and more actionable (via transparent benchmarking), so discovery teams can make
faster, better-informed decisions.

A global research effort

These contributions were developed with academic collaborators across Germany, France, China, and India, eflecting a genuinely international, multidisciplinary collaboration.

Let’s discuss partnerships and strategic opportunities

If you are:

• a pharma/biotech team evaluating generative protein design for discovery programs, or
• a VC investing at the AI × Biology frontier

We welcome discussions on platform partnerships, co–development, and strategic financing.

ICML: https://icml.cc/Conferences/2025
GenBio Workshop: https://lnkd.in/gMcj83tx

For more information:

PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/

🌐PEACCEL at the Cutting Edge of Biopharmaceutical Innovation: Generative AI, Diffusion Models, and Quantum Computing

🔬 PEACCEL unveiled its latest research on Diffusion Models in drug design, providing an in-depth analysis of 56 cutting-edge models and their interconnections. These models, including Score-based Generative Models (SGM) and Denoising Diffusion Probabilistic Models (DDPM), are revolutionizing the design of proteins, peptides, and small molecules. We critically examine the role of E(3) and SE(3) equivariance and symmetry in advancing these methodologies.

PEACCEL’s pioneering work positions it as a leader at the forefront of technology, combining the transformative power of Generative AI, Diffusion Models, and Quantum Computing. These advancements are unlocking unprecedented opportunities for pharmaceutical companies and venture capitalists eager to invest in the next wave of biopharmaceutical breakthroughs.

🤝 For partnerships or investment opportunities, connect with PEACCEL and be part of the future of healthcare innovation.

For more information: https://arxiv.org/abs/2501.02680

PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/

🌐 PEACCEL’s Quantum Breakthrough in Biopharmaceutical Discovery Published in Quantum Information Processing (Springer Nature).

We’re thrilled to announce that our pioneering research paper on Quantum Computing for biologics has been published in Quantum Information Processing! This milestone marks a significant leap forward in pharmaceutical discovery, showcasing the transformative potential of Quantum Machine Learning (QML) in real-world applications.

🧬 The Quantum Leap for Biologics Development

We applied Quantum Support Vector Machine (up to 14 qubits) to classify peptides as hemolytic or non-hemolytic—a critical task with life-saving implications. 

Our work paves the way for faster, safer, and more effective biologics, transforming patient care worldwide.

🔍 Collaborative Excellence

This groundbreaking work was conducted in collaboration with the University of Western Australia’s Quantum Physics and Computing team, under the leadership of Prof. Jingbo Wang.
For more information: https://doi.org/10.1007/s11128-024-04540-5

PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/

We are thrilled to announce that PEACCEL has been awarded the prestigious French DeepTech label by BPI France, the public investment bank dedicated to innovation. This recognition is a testament to our commitment to pushing the boundaries of biotechnology with our groundbreaking AI discovery platform for Biologics.

Continue reading “Unlocking the Future of Pharma: PEACCEL’s Breakthrough AI Platform for Biologics Wins French DeepTech Label.”

Protein engineering in the context of metabolic engineering has a growing impact in industrial biotechnology and synthetic biology. Epistasis is a crucial issue: Non-Linear responses can hinder drug target identification or optimization of industrial production processes.

Discover our Editorial for a special issue of Frontiers in Molecular Biosciences: Machine learning, epistasis, and protein engineering: From sequence-structure-function relationships to regulation of metabolic pathways VOL I.

Read more: https://www.readcube.com/articles/10.3389/fmolb.2022.1098289

For more information:

PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/

Maximize your next value creation opportunity for peptides, proteins, enzymes, antibodies & VHHs.  Stand out of the reach of your competitors.

EPI_technology™ (Epistasis Processing Inside): Unique on the market, better & quicker for protein design & optimization  

Meet Peaccel’s delegates Jean-Marie Vallet and Jacob Weintraub at the Synthetic Biology-Based Therapies Summit, December 14-15 2022, Boston, US: https://synthetic-biology-therapeutics-summit.com

For more information:

PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/

The recent development of structure prediction deep learning (DL) tools such as Alphafold2 (DeepMind), ESMfold (Meta) or ProteinMPNN (David Baker’s team) has revolutionized this area. Nevertheless, these DL tools are not suitable for predicting how individual amino acid changes alter protein function: they can’t predict epistaticeffects.

After protein folding powered by DeepMind and Meta the next challenge is to accurately predict epistasis ie. the impact of non-linear interactions of mutations within the protein sequence on the function.

Our recent review of Machine Learning (ML) and Deep Learning (DL) strategies examines how epistatic effects influence the success rate of protein engineering projects by comparing 15 state-of-the-art approaches (see Table 4: https://link.springer.com/protocol/10.1007/978-1-0716-2152-3_15/tables/4) and provides a general workflow for non-experts when using such learning strategies.

Read more: https://link.springer.com/protocol/10.1007/978-1-0716-2152-3_15#Abs1

For more information:

PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/

Epistasis dramatically influences the success of drug discovery projects: The real lead drug candidate is missed if epistasis is not taken into account.

After protein folding powered by Meta and DeepMind , the next challenge is to accurately predict epistasis ie. the impact of non-linear interactions of mutations within the protein sequence. PEACCEL’s founder, co-authored in ACS Catalysis a critical review on epistasis with its partners at Leibniz Institute of Plant Biochemistry.

Read more: https://pubs.acs.org/doi/10.1021/acscatal.2c01426#

For more information :

PEACCEL
Making the world disease free
Contact: AI-team@peaccel.com
http://www.peaccel.com/