Cord Dohrmann
Analyst · Brendan Smith from TD
Thank you, Paul, and good morning and good afternoon to everybody on the call also from my side. As you know, at Evotec, we strive for technology and science leadership on our mission to pioneer drug discovery and development. Our ambition is to accelerate the journey from concept to cure in partnership with our customers. Today, we are pleased to talk about considerable achievements we have made along this strategy in both segments. Let me start with a look at the D&PD segment first. We are seeing great scientific progress with our strategic partnerships. Based on these achievements, we continue to feed and expand our strategic partnerships and are confident that our common asset pipeline will show substantial progress not only in 2025, but also during the next 6 to 9 months. So what is our approach? Christian already mentioned that we offer end-to-end discovery services, including development and also highly innovative drug discovery technology platforms. We strive to combine both offerings to create superior customer value. Our core service offering spans the entire value chain from target identification to IND. When we combine those individual services, we can seamlessly run integrated research projects using highly automated workflows. This train of services, shown in blue on this chart, is the backbone of our operations. Within our strategic partnerships, we are then adding proprietary AI-enabled technology platforms on top of this. These are shown here in pink. These platforms elevate our drug discovery platforms to the next level. Our AI-driven platforms are targeting, in particular, 4 goals. We create a much deeper understanding of disease biology, and therefore, patient stratification through our proprietary molecular patient database. We improve our target ID and validation efforts as well as hit identification through superior in vitro disease models driven by our iPSC platform. We enhance and accelerate hit to lead and lead up processes through in silico profiling and an eye supported molecular design. We reduce the risk of failures due to industry-leading tox and safety predictive tools. So this means that AI for us is not a stand-alone feature. We have embedded AI deeply into our toolbox, enhancing the performance of each and every platform in the value chain. Based on this, we not only shorten time lines, but we also improve outcomes. Let me briefly take you through the individual elements. Our proprietary molecular patient database consists not only of highest quality and comprehensive clinical data, but also of deep multi-omics data based on corresponding patient samples. This database is invaluable when it comes to target ID and validation and is supported by AI machine learning algorithms. Our E.INVENT platform is a highly comprehensive suite of AI machine learning supported molecular design tools, predicting everything from solubility, ADME-tox parameters, affinities to targets, but most importantly, it supports our -- it accelerates our molecular design cycles. Our AE safety platform is a suite of NAMs consisting of gold standard in vitro models, which are combining with high content omics and/or high content imaging data to predict the safety and tox profiles of drug candidates. We are doing this with extremely high accuracies, and I will come to this in more detail later. Furthermore, we have an extremely versatile iPSC drug screening platform, which in combination with omics and high-content imaging data is able to profile disease relevance as well as efficacy and safety of drug candidates throughout the drug discovery process with higher granularity, and therefore, higher accuracy than standard in vitro models. All of these platforms are underpinned by our seamless high-performance omics platforms, which can generate, in particular, transcriptome, proteome and metabolome data at highest quality and with unmatched throughput. I will come to the details here later as well. Finally, we are able to bring all of these data together in our data analysis tool called PanHunter. This tool facilitates the handling and the analysis of high-dimensional data sets and is in many areas, AI machine learning supported. On the next page, I will show you selected examples of significant scientific achievements in 2025 and also talk about how they translate into commercial results with our strategic partners. And thereafter, I will show you how those partnerships are associated with highly attractive long-term financial upside. But let me take you through a few selected highlights. I have mentioned the importance of our Evotec molecular patient database as a foundation for a better understanding of disease processes, and therefore, also target ID and validation. And in 2025, we have significantly expanded the database through the addition of new cohorts, in particular, in kidney diseases, obesity, but also immunological diseases. This database continues to support strategic partnerships, while also generating multimillion dollar success-based payments. As far as our iPSC drug discovery platform is concerned, we continue to upgrade our disease models into more complex organoid-type in vitro models. We have done this particularly successful in the kidney disease space. We continue to also make progress in our AI-supported small molecule design platform, E.INVENT. Here, we continue to build models that support specifically the design of certain compound classes as we believe that there are no one-size-fits-all models that are suitable for every compound class. We mentioned previously that we continue to invest in new approach methodologies, NAMs, to predict safety and toxicology of drug candidates. Also, here, we continue to make very significant progress by continuously improving our existing models, while also adding further models. For example, our drug-induced liver injury tox prediction tool continues to improve as now we have reached a predictive accuracy of more than 90%. Similarly, we have developed a highly predictive cardiotox prediction tool, which also has a predictive accuracy of about 90% A further example is a new model of a -- in a teratogenicity prediction tool, where we are currently approaching 80% of predictive accuracy. To our knowledge, these omics and image-based AI-supported safety tox prediction tools are absolutely industry-leading when it comes to their predictive accuracies. Finally, I would like to briefly talk about scientific progress in our PanOmics platform. Our high-performance PanOmics platform continues to evolve. In 2025, we reached 2 landmark achievements. With our high-throughput transcriptomics platform called ScreenSeq, we conducted a high-throughput compound screen, screening over 250,000 compounds using transcriptomics as the primary read-out. To our knowledge, this is an industry first and has never been done before. Similarly, we keep improving our proteomics platform. We have improved efficiency, automation and throughput of our platform significantly and expect to profile over 100,000 compounds in 2026 using proteomics as the primary read-out. To our knowledge, there is no other company generating as many proteomic compound profiles in the industry or processing as many samples using proteomics. So it is great to see that we continue to make this much progress on our AI-supported proprietary platform. Just as important is, however, that these platforms continue to support the business financially. The combined order value to these -- directly tied to these AI-powered platforms is currently north of $200 million already. Beyond this, it is important to keep in mind that these platforms are not only supporting the business through research payments, they enable us to build strategic partnerships, which fuel our partnered asset pipeline with very substantial financial upside. And this is shown in more detail on the next slide. Today, Evotec has a pipeline of more than 100 projects. Over 60% of these projects are part of strategic partnership, and therefore, fully supported by these. All of the more advanced assets, in particular, those in clinical and preclinical stages are supported by partnerships, and therefore, represent pure financial upside for Evotec. Collectively, this portfolio represents a non-risk-adjusted value of over EUR 16 billion just in milestones. In 2025, the pipeline progressed significantly, which means that the total milestone potential of more than EUR 16 billion as well as significant royalties is becoming increasingly tangible. Accumulated returns up to 2028 could total on the order of EUR 500 million. In April, we gave you a status update on our asset portfolio. At that time, in total, we had 12 projects of our 100 projects were beyond the discovery stages, 6 of these were in preclinical stages and 6 in clinical Phase I. In 2025, 2 assets have progressed from Phase I to Phase II of clinical development. Furthermore, we expect that 1 asset will move from the preclinic into the clinic. And moreover, we anticipate further progress over the course of the next 6 to 9 months with 2 further molecules expected to move to clinical Phase II. This means that there's a high likelihood that our asset pipeline will have in total 4 molecules in clinical Phase II, each of them with a different partner in different indication areas. Overall, we are clearly pleased with a lot of progress on multiple fronts. First of all, we have very significant scientific progress on AI-supported platforms. We have been able to show very significant progress in our clinical and preclinical portfolio of assets with 2 new assets in Phase II and additional assets expected to come to the clinic soon. And finally, our discovery stage pipeline also continues to expand and is expected to continue to fuel our preclinical stage portfolio going forward. So a lot more exciting news to come here within the next 6 to 9 months. This is where I hand over and back to Christian.