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Life Sciences Data Networks for AI
Co-Folding AI
AIDrugDiscovery
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OpenFold Expands AI for Biological Modeling Mission with Two New Members
Business Wire
Apheris will bring privacy-preserving, AI infrastructure and collaboration on proprietary data to the OpenFold Consortium
AISB Network expands Federated OpenFold3 initiative with three new pharma contributors
Discover Pharma
The AI Structural Biology (AISB) Network, powered by Apheris GmbH, has expanded its Federated OpenFold3 Initiative with the addition of Astex Pharmaceuticals, Bristol Myers Squibb, and Takeda. The new partners join founding members AbbVie and Johnson & Johnson to fine-tune OpenFold3 on proprietary structural datasets.
AISB Network Expands Federated OpenFold3 Initiative with Three New Pharma Contributors
Apheris announced today the expansion of the Federated OpenFold3 Initiative from the AI Structural Biology (AISB) Network.
News
Co-Folding AI
AIDrugDiscovery
Ginkgo Datapoints and Apheris Launch Antibody Developability Consortium
Gingko Datapoints
Ginkgo Bioworks today announced a series of new initiatives from its Datapoints offering to accelerate the application of artificial intelligence in biologics drug discovery. These include a strategic partnership with Apheris to launch the Antibody Developability Consortium and, separately, the AbDev AI Competition.
Federated learning for lesion segmentation in multiple sclerosis: a real-world multi-center feasibility study
Frontiers
In this proof-of-concept work, we aim to apply and adopt Federated Learning (FL) in a real-world hospital setting. We assessed FL for MS lesion segmentation using the self-configuring nnU-Net model, leveraging 512 MRI cases from three sites without sharing raw patient data.
Why co-folding models are here to stay
Co‑folding models, like AlphaFold 3, Boltz‑2, and OpenFold3, can predict the joint 3D structures of two (or more) molecules at the same time. While these models perform well on public benchmarks, they often become less accurate when applied to novel targets underrepresented in the training data.
Co-Folding AI
AIDrugDiscovery
Federated learning-based protein language models with Apheris on AWS
AWS
In collaboration with AWS, we implemented FRA-LoRA (Full Rank Aggregation of Low-Rank Adapters) in a federated setting to fine-tune ESM-2 across multiple sites, all without sharing raw data. LoRA reduced trainable parameters to <2% of the original model, cutting communication overhead while preserving accuracy.
AI for ADMETox predictions: state-of-the-art
BioAscent
In the ever-evolving landscape of drug discovery, understanding how a drug behaves in the body is crucial. In this blog, Dr Angelo Pugliese explores the pivotal role ADMETox plays in this process.
Apheris releases 3.8
Apheris 3.8 improves compute spec management, reduces dependencies for streamlined training, and expands diagnostics, supporting production-scale federated AI in clinical research, multimodal data networks, and computational biology.
release
NVIDIAFLARE
Aggregating Low Rank Adapters in Federated Fine-tuning
arXiv
Fine-tuning large language models requires high computational and memory resources, and is therefore associated with significant costs. When training on federated datasets, an increased communication effort is also needed. For this reason, parameter-efficient methods (PEFT) are becoming increasingly important.
Toward a tipping point in federated learning in healthcare and life sciences
Patterns (a Cell Press journal)
We discuss the real-world application of federated learning (FL) in the healthcare and life sciences industry, noting a tipping point in its adoption beyond academia.
Secure AI Collaboration Will Fine-Tune OpenFold3 with Proprietary Data
Genetic Engineering & Biotechnology News
In a new initiative by the AI Structural Biology (AISB) Consortium and powered by Apheris, OpenFold3, a protein structure prediction algorithm developed by the lab of Mohammed AlQuraishi, will be fine-tuned using proprietary data from AbbVie and Johnson & Johnson.
AbbVie, J&J to add proprietary data to AIprotein model in bid to accelerate drugdiscovery
STAT
AbbVie, J&J to add proprietary data to AIprotein model in bid to accelerate drugdiscovery. OpenFold3 will access the companies’ data using federation technology from Apheris
AlphaFold is running out of data - so drug firms are building their own version
Nature News
Thousands of 3D protein structures locked up in big-pharma vaults will be usedto create a new AI tool that won’t be open to academics.
Apheris releases v3.7 – ESM-2 8m, custom-model workflow and much more
v3.7 is here, bringing expanded Python and NVIDIA FLARE support, a more streamlined model management experience, and improvements across the board for Data Scientists and Data Custodians.
release
Computational governance
AlQuraishi lab’s OpenFold3 to Be Fine-Tuned with Pharma Industry Data in a Secure AI Collaboration Powered by Apheris
OpenFold3, a structure prediction system developed by AlQuraishi Lab at Columbia University, will be fine-tuned using proprietary data from AbbVie and Johnson & Johnson in a confidentiality-preserving and secure federated environment powered by Apheris.
AIDrugDiscovery
Pharma
News
Apheris Achieves SOC 2 Type I Attestation – Reinforcing Our Commitment to Security
Apheris achieves SOC 2 Type I attestation, reaffirming its commitment to data security and privacy, and the comprehensive measures we have implemented to protect sensitive information and ensure the highest level of security.
Security
Platform & Technology
Apheris Launches Trust Center, Elevating Security and Data Privacy Standards
The Apheris Trust Center serves as a comprehensive resource for organizations seeking to uphold the highest standards of security and data privacy. It offers guidance and our certifications and attestations, including ISO 27001 and SOC 2, that customers value as essential components to fulfil their compliance obligations.
Security
News
AI regulation: Why it needs to come sooner rather than later
"As AI adoption gathers momentum, it is essential we get in front of this generational technology and regulate it in a way that works for everyone – before it is too late."
Machine learning & AI
Privacy
Apheris Compute Gateway - Let's collaborate.
Apheris Compute Gateway 3.0 provides an end-to-end federated analytics and machine learning solution that enables everyone to collaborate securely on highly sensitive data.
Computational governance
Security
News
Apheris achieves top information security certification, ISO 27001
Certification highlights our mission and focus on best practices for federated machine learning and analytics, enabling organizations to securely build and operationalize machine learning and data applications across boundaries.
Regulation
News
Apheris raises €8.7m to power development of smarter AI and collaboratively solve the world’s biggest challenges
Seed extension round led by Octopus Ventures to drive growth of platform enabling organizations to unlock terabytes of valuable data risk-free
News
Computational governance
Apheris completes SOC2 Type2 Attestation
Berlin 09.03.2025 - Apheris has successfully completed SOC 2 Type II attestation, confirming that our controls for data protection, security, and privacy adhere to recognized industry standards.
Regulation
Security
Apheris launches platform to unlock data and enable collaboration to solve the world’s biggest problems
The Apheris Platform enables multiple organisations to extract value from each other’s decentralised data sets and overcome regulatory, technical, and commercial challenges.
Platform & Technology
Security
Apheris 3.6: Chaining, Governance, and More!
This release introduces the magic of chaining Derived Datasets, levels up model management in the Governance Portal, and fine-tunes the Apheris Model Registry. Let’s crack open the details.
release
Pharma
Computational governance
3.5 – Adding XGBoost, BERT, and Apache Parquet Support
The new version, 3.5, is packed with new goodies and improvements to make your federated life easier and protecting your data assets even more convenient. Read more
Computational governance
Security
Collaboration
Apheris announces Series A fundraise to power the world’s leading life sciences data networks
Apheris has closed a Series A funding round, raising total funding to $20.8M. Led by OTB Ventures and eCAPITAL, this round will help Apheris to expand its secure life sciences data networks.
AIDrugDiscovery
Pharma
News
What is a Federated Data Network and How Does it Support Cross-institutional Research?
A federated network is defined as a network that spans across geographical or organizational boundaries. Such a federated network contains interconnected nodes that are operationally independent, yet centrally managed for efficiency and ease of use. A federated data network is
AIDrugDiscovery
Pharma
Federated learning & analytics
Apheris 3.4 – Getting better, one release at a time
With today's release, we continue our journey to provide the simplest, most secure solution for building and joining data networks in life science and drug discovery.
release
Platform & Technology
Federated learning & analytics
Observations from the Drug Discovery Innovation Forum 2024
Pharma and biotech companies often lack enough data within their own organizations, limiting AI model accuracy. Read more about my discussions with pharma leaders at this years Drug Discovery Innovation Forum DDIF on overcoming the data access dilemma.
AIDrugDiscovery
Pharma
Healthcare
Collaborative AI for Pharma
Secure data collaboration brings new capabilities to the pharama and biotech community. Read about applications, use cases and challenges in collaborative settings and how Apheris can help.
Pharma
Healthcare
Collaboration
Federated learning & analytics
Apheris 3.3 – Improved scalability & Federated Logistic Regression
Great news, everyone! We released Apheris 3.3. With prior releases, we set the foundation for two really useful improvements for our users today — derived Datasets and Multi-Gateway Organizations.
release
Platform & Technology
Federated learning & analytics
Apheris joins the Global Alliance for Genomics & Health
We are excited to announce that Apheris has officially joined the Global Alliance for Genomics & Health (GA4GH) as an organizational member.
Healthcare
News
Collaborative data ecosystems
Managing Github as code: A DevSecOps approach
Our journey to secure and standardize GitHub repository configurations at Apheris using Infrastructure-as-code.
Security
Platform & Technology
Federated Learning and Data Mesh: how it enhances data architecture
Federated Learning and Data Mesh enable decentralized model training with domain-specific governance. This integration improves data privacy, scalability, and regulatory compliance, addressing limitations of traditional systems in regulated sectors where sensitive data is involved.
Data & analytics
Collaboration
Data collaboration vs data sharing: Everything you should know
Discover why data collaboration is the future. Explore how federated learning keeps data safe while promoting collaboration without sharing.
Collaboration
Collaborative data ecosystems
Apheris 3.2 released - Federated nnUnet & Cox Regression; Simplified Data Science Experience
Apheris Compute Gateway 3.2 provides a simpler way to create federated computations, adds federated nnUnet and cox regression and streamlines the data science experience.
Data & analytics
Data science
release
Apheris Compute Gateway - Let's collaborate.
Apheris Compute Gateway 3.0 provides an end-to-end federated analytics and machine learning solution that enables everyone to collaborate securely on highly sensitive data.
Federated learning & analytics
Computational governance
Pharma
AIDrugDiscovery
NVIDIA
NVIDIAFLARE
release
Top 7 Open-Source Frameworks for Federated Learning
Open-source frameworks for federated learning are a great way of getting first hands-on experience. Here are our Top 7 with their respective pro and cons
Collaboration
Machine learning & AI
How privacy-enhancing technologies can help you achieving data privacy in enterprise ML/AI
Discover the power of Privacy Enhancing Technologies (PETs) and why they're crucial for your enteprise ML/AI projects involving sensitive or regulated data. We'll demystify PETs with clear examples, equipping you with the knowledge to make informed decisions on how to best protect your data and enhance your products.
Privacy
Machine learning & AI
Federated learning trends: from academic insights to industry applications
In December, the annual NeurIPS conference took place. With the biggest conference in machine learning research happening, I was curious to see what was going on in the world of federated learning. Here are my 5 take-away on how federated learning can be applied in industry today.
Federated learning & analytics
Machine learning & AI
Computational governance: The key to building safe and compliant AI
techradar.pro
Computational governance could be the key to AI safety.
The stakes are becoming increasingly high for companies developing AI in highly-regulated industries. In sectors such as healthcare and finance, compliance is not just a legal obligation, but a crucial aspect of building trust and integrity.
Computational Governance & healthcare data: pioneering new frontiers within regulatory boundaries
Computational governance enables machine learning on European healthcare data.
European hospitals face a unique challenge, balancing complex regulatory frameworks with the need to make valuable data available for research. Computational governance exists as a solution and enables compliant research on health data.
Computational governance
Platform & Technology
Healthcare
The Future of AI: Capitalising the value of proprietary data
EU-Startups
Apheris Co-founder and CEO, Robin Röhm, discusses how data is the lifeblood of AI. Those who produce, own, or control access are critical stakeholders. However, they face a paradox: They must protect their organization’s sensitive data, but in doing so, they act as a blocker to realizing the potential of that data for ML and AI.
How CISOs Can Enable Productization of Valuable Data Assets
InsideBigData
Ellie Dobson, VP Product at Apheris, discusses how the rapid adoption of ML has led to data becoming one of the most valuable assets in business. However, for use cases where compliance with regulation and data privacy is of paramount importance, unlocking the full potential of data raises unique challenges.
German antitrust leader warns AI may boost Big Tech dominance
Verdict
In this article, Robin Röhm, CEO Apheris, comments on the relationship between data and AI: “... AI is nothing without the data that is used to feed its machine learning algorithms...There is a monopoly of power that comes with AI and data accessibility,” he said
Navigating the compliance maze in AI development
As AI reshapes many industries, the balance between innovation, security, and compliance has become paramount, especially in regulated sectors.
Regulation
Computational governance
Machine learning & AI
Federated learning & analytics
Stop talking, start doing – AI regulation is coming and you need to be ready for it
EU-Startups
While governments around the world are laying out plans to regulate AI, many businesses are woefully underprepared for the complexity of what lies ahead. With regulation about to roll through jurisdictions across the world, it is time to stop talking about what it might look like – and start acting.
Governed, secure, and private computational access to federated patient data is revolutionizing healthcare AI
MedTech AI revolution depends on computational access to fine-grained patient data to train enhanced ML models. Apheris provides governed, secure, and private computational access to data for ML, enabling fast and easy FDA approval for new MedTech data products.
MedTech
Regulation
Computational governance
Security
Data & analytics
The EU AI Act: Understanding and Preparing for Compliance
Exploring the EU AI Act, a pivotal regulation addressing AI's multifaceted nature, this blog outlines risk levels, high-risk system requirements, and preparation for compliance. Apheris's solution for various governance, privacy, and security obligations is highlighted, emphasizing a shared commitment to responsible AI.
Regulation
Machine learning & AI
Platform & Technology
Will the NHS Federated Data Platform transform UK healthcare?
IT Pro
Plans to create a data platform in partnership with the private sector could revolutionize NHS treatment, but concerns over data privacy and security are festering
Hey, your data is on mute
Reaching universal agreement on how to regulate AI is impossible. But a carefully designed cyclical process can lead to efficiencies in an enterprise's journey towards trustworthy, accountable, and sustainable AI. In this blog, I navigate the regulation space through the eyes of a data custodian.
Working at Apheris
Data & analytics
Collaboration
Privacy
Machine learning & AI
Federated learning & analytics
Enlightening Dark Data
There is so much useful data around us. Yet most data is not accessible for machine learning or other large scale analytics. In this article, we will explore why this is and what needs to be in place to enlighten this dark data.
Collaboration
Collaborative data ecosystems
Privacy
EU AI Act: How AI regulation could affect your startup
EU-Startups
With the EU AI Act imminently being finalised and countries like the UK and the US recently publishing their national AI development strategies, the topic of regulation is being hotly debated.
Enabling IP-Preserving Computations on Sensitive Data
Machine learning and AI needs domain-specific data to be trained for its various use cases. Often this data is sensitive and falls under various privacy regulations. In this article we will introduce the Apheris Compute Gateway as a solution for contributing sensitive data to ML projects.
Security
Data & analytics
Collaboration
Privacy
Machine learning & AI
Platform & Technology
The Rise of Federated Learning: Top 5 Federated Learning Startups
Companies are benefiting from federated learning by being able to access data without privacy and IP risks associated with copying or centralizing data.
Machine learning & AI
Federated learning & analytics
Sunak’s challenge is to design flexible but firm rules for artificial intelligence
City A.M.
ChatGPT has thrown artificial intelligence into the mainstream, and now it’s Rishi Sunak’s job to design rules which don’t prevent its growth, but keep us safe, writes Robin Röhm.
Delivering maximum social benefit from artificial intelligence (AI): Leveraging its capabilities responsibly
AI safety is not a future problem to solve, it’s a real problem right now. In this blog I'll explain the challenges we face as a society in developing and using AI, and propose some operating principles to help us leverage AI for social good.
Collaboration
Privacy
Machine learning & AI
Federated learning & analytics
We have to act now - how to take a responsible approach to sustainability as an organization
The clock is ticking. The time to act on climate change is now. In this blog, I'll take a closer look at practical thoughts on climate thinking and action in organizations.
Working at Apheris
Sustainability
The UK has gone rogue with its AI policy
Sifted
AI regulation looks like the next continental differing of opinion — here's why the UK's approach could affect the rest of the Europe.
AI regulation: Why it needs to come sooner rather than later
The AI Journal
AI development is happening at breakneck speed, underpinned by massive investments from Big Tech companies such as Microsoft, Google and Amazon...But AI regulation need not be an obstruction to innovation.
Securing ML Models: Apheris' Contribution to ML Security
Together with the German Federal Office for Information Security we've developed frameworks and recommendations for ML practitioners to help secure ML models and maintain appropriate security measures.
Security
Privacy
Challenges with implementing federated learning
Explore some of the common challenges organizations face when implementing federated learning and key considerations that can help them overcome those challenges and reap the rewards of working with federated data.
Federated learning & analytics
Data & analytics
Collaboration
Celebrating women's contribution to STEM fields
11 February is the International Day of Women and Girls in Science. We interview Evelyn, Data Science Experience Lead at Apheris, and give you an insight into the life of a successful woman in science.
News
Events
Working at Apheris
Data science
US-EU Artificial Intelligence agreement proves there’s no time to wait for companies to act on AI regulation
tech.eu
Robin Röhn, CEO and co-founder and Berlin-based Apheris weighs in on what the US-EU artificial intelligence collaboration agreement means going forward, including what's sure to be a growing call for increased regulation.
How to collaborate without sharing data
InfoSecurity Magazine
Organizations are sitting on terabytes of data that only they can access. While it is highly valuable when used to inform key decisions for an individual company, the true power of data lies in collaboration between organizations.
Security of AI  Systems: Fundamentals
Advising the German Federal Office for Information Security on the Security of AI-Systems, Apheris provides an overview on attack vectors and threats of AI systems where external data is used or trained models are exposed to third parties. Recommendations are derived on how to systematically safeguard and test AI-systems.
Big Tech’s thirst for data is behind Microsoft’s investment in the London Stock Exchange Group
The AI Journal
Microsoft’s recent purchase of a £1.5bn stake – equivalent to 4% – in the London Stock Exchange Group (LSEG) was the latest deal to unite Big Tech with a business running one of the world’s most significant financial markets.
Meet Robin Röhm, CEO and Co-Founder at Apheris
TechRound
Apheris is a platform for creating collaborative data ecosystems. The platform enables multiple organisations to extract value from each other's decentralised data sets, without changing the data’s location or sharing it.
Letters: A GDPR Brexit won’t help us
City A.M.
The announcement this week by culture secretary Michelle Donelan that the UK plans to replace GDPR with its own “business and consumer-friendly British data protection system” is bad news. It will only increase complexity for companies in Britain and the EU hoping to collaborate by sharing data across geographical boundaries...
UK to replace GDPR with ‘consumer-friendly’ privacy regime
AI Business
New culture secretary decries ‘red tape,’ but detractors warn complexity could arise.
The U.K. government plans to scrap the General Data Protection Regulation (GDPR), the EU’s data privacy regime it adopted before leaving the union.
Donelan hints at replacing GDPR with British alternative
Computing
The UK currently holds a data adequacy agreement with the EU, enabling cross-border data flows. Any moves that threaten to disrupt that trade must be considered carefully and without ideology.
MBeacon: Privacy-Preserving Beacons for DNA Methylation Data
The advancement of molecular profiling techniques fuels biomedical research with a deluge of data. To facilitate data sharing, the Global Alliance for Genomics and Health established the Beacon system, a search engine designed to help researchers find datasets of interest.
Asymmetric Private Set Intersection and Private Vertical Federated Machine Learning
We present a multi-language, cross-platform, open-source library for asymmetric private set intersection (PSI) and PSI-Cardinality (PSI-C). Our protocol combines traditional DDH-based PSI and PSI-C protocols with compression based on Bloom filters that helps reduce communication in the asymmetric setting.
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
We introduce PyVertical, a framework supporting vertical federated learning using split neural networks. The proposed framework allows a data scientist to train neural networks on data features vertically partitioned across multiple owners while keeping raw data on an owner's device.
Apheris' first carbon removal purchases
Our focus on sustainability extends beyond the impact we have on our customers, and our environmentally conscious mindset is at the core of Apheris’ work culture.
News
Working at Apheris
7 Myths About Federated Learning
In our daily work as a company that builds a platform for federated and privacy-preserving data science, we are often asked to clarify concepts around federated learning with customers. This article highlights 7 common myths about federated learning (FL) and, using practical examples, shows you exactly why they are misleading.
Data & analytics
Federated learning & analytics
Machine learning & AI
How to Choose the Best Federated Learning Platform
How can you evaluate platforms around emerging technologies like federated learning? This article gives you guidance on what your selection criteria should be.
Data & analytics
Collaboration
Platform & Technology
Federated learning & analytics
Data science
Privacy
The Three Adoption Stages of Privacy-enhancing Technologies (And Why We Are Stuck on Level Two)
PETs are massively changing how we operate, and how we have to think about the data and AI landscape. Introducing such a game-changer into large enterprises has to be done with the highest precision, and a lot of foresight.
Collaboration
Data & analytics
Platform & Technology
Privacy
Machine learning & AI
Federated learning & analytics
Data science
Collaborative data ecosystems
7 Value Drivers of Complementary Data - Your Path to Unlocking the Benefits of Federated Data
There is only value in data if it can be used, and if there is appropriate access to that data when it is needed. Learn how you can turn decentralized, federated data into a complementary strategic data asset.
Platform & Technology
Collaborative data ecosystems
Data & analytics
Collaboration
Federated learning & analytics
What Are Collaborative Data Ecosystems in the Context of PharmaCos?
Collaborative data ecosystems in pharma securely connect life sciences and healthcare data to drive AI-powered insights or advanced analytics on these distributed datasets. They enable shared use of real-world data without exposing sensitive information, overcoming data silos while ensuring privacy and compliance.
Data & analytics
Collaboration
Platform & Technology
Privacy
Machine learning & AI
Federated learning & analytics
Data science
Collaborative data ecosystems

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