The Blog

pmwc 2025 brought together a diverse mix of experts—data scientists, platform companies, researchers tackling rare diseases, investors, and non-profit organizations—all focused on advancing precision medicine. arnout van hyfte, head of products & platform at mindwalk, and dr. shuji sato, vp of innovative solutions at ipa, represented our team at pmwc 2025, diving into engaging discussions with researchers, industry leaders, and innovators. arnout took the stage at the ai & data sciences showcase, sharing practical insights on how blending ai with in vivo, in vitro, and in silico workflows is reshaping drug discovery, making it more efficient and data-driven. what everyone was talking about one of the hottest topics at pmwc 2025 was the importance of accurate and rapid diagnostic assays, where antibodies could deliver the required specificity and sensitivity. there’s a growing need for high-quality antibodies to detect disease biomarkers, generating richer datasets that provide deeper insight into disease progression. but as the complexity of data increases, managing and integrating it efficiently becomes just as critical as generating it. arnout van hyfte from mindwalk, presenting "accelerating drug discovery: integrating in vivo, in vitro, and in silico workflows" the shift to single-cell techniques we’re seeing a clear shift in how researchers are characterizing patients. dna and rna sequencing have become standard tools, and the next big step is single-cell analysis. by examining patients at the cellular level, researchers can better stratify diseases and develop more precise treatments. but working with this level of detail comes with challenges—more data means more complexity. this is where smarter data integration becomes crucial. making sense of diverse datasets and identifying meaningful connections can lead to faster, more effective decision-making in drug development. at mindwalk and ipa, we’re helping researchers turn raw data into actionable insights by linking diverse biological data layers seamlessly. making sense of complex data and targets as drug discovery advances, researchers are dealing with increasingly complex human targets that don’t have straightforward animal model counterparts. this is where making sense of vast amounts of biological data becomes even more crucial. biostrand’s hyft™ technology plays a key role here—linking sequence data to structural and functional information to map complex relationships across life science data layers. by integrating hyft with ai models, researchers can explore deeper biological insights that support target identification and validation. in silico techniques enable the construction of surrogate models that represent intricate disease pathways, aiding preclinical development while optimizing time and resources. combined with hyft-driven insights, this approach helps refine drug discovery strategies. precision is also essential in antibody discovery. the demand for highly specific and sensitive antibodies continues to rise, not just for diagnostics but also for reagents that keep pace with technological advancements in screening and disease characterization. engineering these antibodies to work effectively in a single iteration helps ensure they keep up with the latest screening technologies and research needs. arnout van hyfte, head of products & platform at mindwalk, and dr. shuji sato, vp of innovative solutions at ipa a future built on collaboration pmwc 2025 wasn’t just about the science—it highlighted the shift toward end-to-end models in the industry. platform companies are seeking collaboration, researchers need more integrated solutions, and the focus is increasingly on seamless, end-to-end approaches. at mindwalk and ipa, we’re bridging the gaps in drug discovery by combining ai, in silico modeling, and deep biological expertise. the key takeaway from this year’s conference? precision medicine isn’t just about data—it’s about making that data work smarter for better, faster discoveries. let’s talk about how we can support your research. reach out and let’s explore new possibilities together.

at ipa 2024 techday, some of the brightest minds in antibody development came together to explore the breakthroughs that are redefining the field. together with ipa, we showcased how our expertise and the innovative lensai platform are tackling some of the toughest challenges in drug discovery. here’s a look back at the event, the insights shared, and the technology driving the future of antibody development. what is lensai? dr. dirk van hyfte, co-founder of mindwalk, introduced the lensai platform by explaining how it’s built on first principles. this isn’t just another incremental improvement—it’s a rethink of how we approach antibody discovery. the platform breaks down traditional assumptions, combining advanced ai with proprietary hyft patterns. the result? a system designed to make therapeutic antibody development faster, safer, and more precise. tackling the biggest challenges in antibody discovery fragmented data: antibody development often involves piecing together data from multiple sources—clinical notes, patents, omics data, and more. lensai simplifies this by bringing it all together in one framework. ai transparency: many ai tools are “black boxes,” leaving users unsure how decisions are made. lensai puts results into clear context, allowing researchers to trace outcomes back to their inputs. speed and scalability: processing millions of sequences can take weeks. lensai does it in minutes, offering real-time insights that keep projects moving forward. fig.1. core challenges in drug discovery how lensai is transforming the antibody development process identifying targets: lensai combines data from clinical reports, unstructured texts, and experimental findings to help researchers zero in on the right disease targets. tools like alphafold enhance this with 3d structure predictions. expanding hits: when you have a handful of promising antibody candidates, lensai takes it further—finding additional functional variants that might have otherwise been missed. this reduces timelines dramatically, often by as much as 300%. mapping epitopes and screening for immunogenicity: by clustering antibodies based on where they bind and screening for immunogenic hotspots, lensai provides clarity early in the process. this ensures candidates are not only effective but safe for clinical trials. fig. 2. lensai powered by patented hyft® technology the secret sauce: integrating in silico and wet lab approaches one of the biggest takeaways from techday was how lensai complements traditional wet lab workflows. ipa has a wealth of expertise in the use of rabbits in antibody development. rabbits might not be the first animal you think of for antibody research, but they offer some incredible benefits. dr. shuji sato walked us through their unique biology: higher diversity: rabbits have a broader antibody repertoire than rodents, which is essential for producing high-affinity, highly specific antibodies. proven success: rabbit antibodies have already been used to develop therapeutic and diagnostic antibodies, including treatments for macular degeneration and migraines. fig. 3. source: https://www.abcam.co.jp/primary-antibodies/kd-value-a-quantitive-measurement-of-antibody-affinity by combining in silico tools with advanced wet lab techniques, researchers can: quickly identify promising candidates. deepen the analysis with structural, functional, and sequential insights. streamline processes like humanization and immunogenicity assessment to save time and reduce costs. this hybrid approach is changing the game for drug discovery. fig. 4. rabbit b cell select program the bigger picture: data-driven decisions in precision medicine during the day’s discussions, one theme came up repeatedly: the importance of better data. as dr. van hyfte put it, “if you want better drugs, you need better data integration.” lensai does just that by harmonizing clinical, genomic, and proteomic data. this helps accelerate drug development while aiming to improve precision and minimize side effects, particularly in areas like oncology and personalized medicine. fig. 5. fully-integrated therapeutic end-to-end lead generation workflow what’s next? the momentum around lensai and our integrated approach to antibody development is only growing. over the next few months, we’ll be rolling out new applications and use cases to support researchers and organizations pushing the boundaries of discovery. if you missed techday, don’t worry! we’ve prepared an interactive demo that walks you through the power of lensai. check it out here. watch all the sessions here. conclusion a huge thank you to everyone who joined us at techday and contributed to the discussions. it’s clear that we’re at a turning point in antibody development—and we’re excited to see what the future holds. if you’re interested in learning more or exploring how lensai can help your research, don’t hesitate to reach out.

the convergence of artificial intelligence and life sciences continues to reshape the biotechnology landscape, as evidenced at this year's biotechx 2024 conference. the event brought together an impressive array of data scientists, ai specialists, bioinformaticians, healthcare, pharma, and life science professionals, showcasing how the integration of ai is revolutionizing every stage of the life science value chain, from early discovery to post-approval processes. the dispersion of ai in life sciences unsurprisingly, there was a lot of emphasis on the value of including ai in the loop. but perhaps one of the most striking observations from this year’s conference was the sheer diversity of ai applications across the biosciences sector. ai-driven technologies are no longer confined to specialized research areas. instead, ai has become an integral tool throughout the entire life science ecosystem. the presentations demonstrated compelling use cases, across critical drug discovery and life sciences r&d processes, where the efficient integration of ai has resulted in significantly enhanced outcomes. to highlight just a few standout use cases: clinical trial optimization: ai-powered solutions are streamlining and expediting patient recruitment and retention, reducing sign-up times, and improving trial efficiency. personalized medicine: ai is driving the shift towards precision healthcare, enabling the creation of more individualized treatment plans by analyzing large-scale patient data, genetic information, and clinical outcomes to optimize therapeutic approaches. molecular engineering: ai is revolutionizing the development of therapeutic antibodies, generating variants with the desired binding properties and potentially superior efficacy. these examples are but a few highlights of how ai is delivering tangible value and measurable improvements in both research outcomes and operational efficiency. arnout van hyfte, head of products & platform | dirk van hyfte, head of innovation | ingrid brands, general manager a unified approach: ipa's in vitro, in vivo, and in silico integration at ipa and mindwalk, we take the integration of in vitro, in vivo, and in silico approaches to heart when it comes to ai-driven cultural transformation. the seamless integration of these disciplines fosters a holistic view of drug development and antibody discovery, allowing us to provide a comprehensive solution that connects biological, computational, and experimental strategies. this methodology not only enhances collaboration but also aligns with the cultural shift needed to fully leverage ai in life sciences. the architecture for ai innovation a significant portion of the conference focused on the architectural frameworks necessary to support effective and scalable ai deployment. many organizations have invested heavily in establishing robust ai-powered data integration and management systems and continuous integration/continuous deployment (ci/cd) pipelines to extract value from that data. yet, a persistent challenge remains: bridging the gap between vast data lakes and the specific needs of individual applications. this is where solutions like the lensai foundation model can enable a transformational impact. by serving as an intermediary layer between raw data repositories and application-specific needs, such foundation models can help organizations transform their data into analytics-ready formats. this architectural approach can be crucial for organizations looking to extract maximum value from their data assets while maintaining flexibility and scalability. cultural transformation: the human element perhaps the most insightful discussions at biotechx 2024 centered around the organizational and cultural aspects of ai implementation. successfully integrating ai into life science organizations requires more than just technical infrastructure and should be accompanied by a fundamental shift in how different specialists, from biologists to informaticians, collaborate. some of the key themes that emerged in this context include: early engagement: proactively fostering collaboration between biological and computational experts from the earliest stages of planning and design can have a positive influence on the algorithmic approach, data visualization, and refinement of analysis. value-driven: clear definition and alignment on project value propositions will be critical to defining focus and maintaining momentum. shared accountability: ai-powered projects will thrive when both biological and computational teams share responsibility for outcomes. the emphasis on cultural transformation also accentuates the importance for life science organizations to develop a "hybrid culture" that bridges the traditional divide between wet-lab biology and computational sciences to create an environment where both disciplines can thrive and complement each other. looking ahead biotechx 2024 made it clear that the future of life sciences lies at the intersection of biological expertise and computational innovation. as we move forward, organizations that can successfully blend technical/technological excellence with a hybrid organizational culture that fosters collaborative, multidisciplinary research will be best positioned to leverage ai's transformative potential in the life sciences sector. want more insights? explore our takeaways from biotechx 2023 and biotechx 2022