Uncovering Novel Drug Targets for Autoimmune and Inflammatory Diseases

Evotec SE, Manfred Eigen Campus, Essener Bogen 7, 22419 Hamburg, Germany (Corporate Headquarters) info@evotec.com | www.evotec.com Uncovering novel targets to boost regulatory T cell phenotype Poster II.517 Abstract# 2888 Ariane Walsh1 , Marina Kramer 1 , Miriam Prohaczka1, Bianca Giuliani 1 , Maiara Severo-Witte 2 , Jan Wahmes 1 , Kamran Honarnejad1 , Hauke Cornils 1 , Markus Dangl 2 1 Evotec SE, Hamburg, Germany; 2 Evotec International GmbH, Göttingen, Germany Pipeline platform Modality Indication space TV Hit ID-H2L LO MytomAb platform Asset 1 Bispecific antibodies for enhanced cell depletion Rheumatology Gastroenterology Asset 2 Rheumatology Gastroenterology Asset 3 Fibrotic disease MApyl for AI/ML driven design Asset 4 Smal molecule inhibitor Gastroenterology FFmAb antibody screening platform Asset 5 Blocking antibodies Rheumatology Gastroenterology Dermatology Asset 6 E.MPD Asset 7 Small molecule inhibitor Rheumatology Gastroenterology Fibrotic diseases Treg CRISPR screen Target ID screen; modality-agnostic Target-dependent HPF transcriptomic screen Small molecule screen to reverse fibrosis Fibrotic diseases Hit-to-Lead entry Lead compound optimization Lead antibody optimization Lead antibody identified Target validation Target deconvolution & validation Optimized core molecule Optimized core molecule Optimized core molecule iPSC-derived cell therapy programs: Cell Type MoA Indication space iT cells Reset of pathogenic B cell compartment Rheumatology; Antibody-driven diseases iMACs Elimination of fibrogenic myofibroblasts Fibrotic diseases Our scientific foundations for co-creating next-generation therapeutics. • We harness Evotec’s fully integrated, end-to-end R&D platforms and deep therapeutic area expertise to enable novel approaches and accelerate the development of drug candidates targeting autoimmune and inflammatory diseases. • By combining our internal R&D efforts with strategic partnerships we co-create and advance cutting-edge therapeutic pipelines in I&I across diverse modalities, including small molecules, biotherapeutics, and iPSC-based cell therapies. Tables: Our internal I&I portfolio available for strategic partnering and licensing opportunities. Evotec’s Inflammation & Immunology (I&I) portfolio PD-1 CD25 FoxP3 CTLA-4 FoxP3 Ki67 viability Increase in FoxP3+ Tregs No change in FoxP3+ Tregs Decrease in FoxP3+ Tregs Significant change in the % of FoxP3+ Tregs after target KO: Figure 2: Scaled expression levels of FACS markers in total CD4+ T cells after target KO: FoxP3, viability (both measured as %), CTLA-4, PD-1, CD25 and Ki67 (all measured as median fluorescence intensity (MFI)). The CRISPR screen FACS read-outs reveal candidate regulators of the Treg phenotype. The “Druggable Genome” screen in total CD 4+ T cells identified: • 453 candidate genes whose KO significantly increased the proportion of FoxP3+ cells (blue dots); the genes represent potential targets to inhibit, block or degrade for the treatment of autoimmune and inflammatory diseases. • 321 candidate genes whose KO significantly decreased the proportion of FoxP3+ cells (red dots); these genes represent potential targets to inhibit, block or degrade for immuno-oncology applications. • In addition to FoxP3 expression, the screen assessed changes in key Treg-associated markers (CTLA-4, PD-1, CD25), proliferation (Ki67), and cell viability following gene KO. Our modality-agnostic CRISPR-based screening platform for the identification of novel Treg phenotype modulators Regulators of Foxp3 as a promising approach to treat autoimmune diseases​. • Regulatory T cells (Tregs) are essential for maintaining immune homeostasis and self-tolerance. Their development and function are regulated by the transcription factor forkhead box P3 (FoxP3). • Treg deficiency or dysfunction is implicated in a range of autoimmune and inflammatory diseases. However, therapeutic modulation of Tregs remains challenging due to a lack of therapeutic targets. • To overcome this, we established a modality-agnostic CRISPR/Cas9-based target identification platform in primary human CD4+ T cells, enabling the discovery of novel regulators of FoxP3 for potential therapeutic intervention. Figure 1: Workflow of Evotec’s CRISPR/Cas9 technology screening platform in primary human T cells • Isolation of total CD4+ T cells from healthy donors • Overnight T cell activation • “Druggable genome” CRISPR library (~8000 genes) • Arrayed format; pool of 4 gRNAs/target • CRISPR/Cas9 KO using RNP transfection by electroporation Cell isolation 1. CRISPRediting 2. FACS read-out 4. • Seven-colour FACS read-out • Hit ID was done based on the frequency of FoxP3+ Tregs in total CD4+ T cells • Primary hits were identified, for which target knockout (KO) led to a significant increase in Tregs Cell culture 3. • Five-day culture using two different media conditions: 1. Maintenance of Tregs (non-inducing; nTregs) 2. Low sub-optimal induction of FoxP3 (iTregs) FoxP3 CD4 nTreg iTreg In vitro assays validate target impact on Treg phenotype and function Selected targets for which the KO increased FoxP3+ cells were further analyzed for genotype-phenotype correlations and associated cytokine profiles. • CRISPR editing efficiencies of selected gRNA pools in CD4+ T cells were assessed by multiplexed targeted amplicon sequencing (rhAmp-seq, IDT). 90% of samples showed >90% efficiency; 97% exceeded 70% efficiency (Figure 3). • We could confirm genes from the screen for which the KO not only enhanced FoxP3 expression across multiple tested donors but also upregulated other Treg relevant markers as well as cytokines such as IL-10 (Figures 4-6). 3 4 5 6 7 3 4 5 6 7 0 1 2 3 4 5 days post CRISPR fold change vs. non-targeted control % viable CD4 T cells % FoxP3+ Tregs 3 4 5 6 7 3 4 5 6 7 3 4 5 6 7 3 4 5 6 7 0 1 2 3 4 5 days post CRISPR fold change in CD4 T cells vs. non-targeted control MFI CD25 MFI CTLA-4 MFI PD-1 MFI TIGIT Figure 5: Changes in FoxP3, CD25, CTLA-4, PD-1, TIGIT, and cell viability in CD4+ T cells on different days following KO of a target identified in the screen (FACS). 3 5 3 5 3 5 0 1 2 3 4 days post CRISPR fold change vs. non-targeted control% IFNg % IL-10 % IL-17A Figure 6. Cytokine production (IFN-γ, IL-10, IL-17A) by CD4+ T cells on different days post-KO of one identified target, measured by intracellular flow cytometry following PMA/ionomycin stimulation. Non-targeted control Targeted KO FoxP3+ FoxP3+ Figure 4: FoxP3 expression (FACS) and IFN-γ, IL-10 and IL-17A cytokine release (FluoroSpot) by CD4+ T cells 5 days after CRISPR target KO of one target identified in the screen. Figure 3: CRISPR editing efficiency (In/Del analysis) of gRNA pools targeting 53 genes (blue circles) in primary CD4 T cells of 4 donors. Conclusion • Evotec has established a robust CRISPR-based screening platform capable of target identification and validation in primary human T cells at scale. • This platform enabled the discovery of novel regulators of the Treg phenotype, offering promising entry points for drug discovery. • These targets may be leveraged across multiple therapeutic modalities, including small molecule inhibitors, protein degraders, and function-blocking antibodies, for the treatment of autoimmune and inflammatory diseases. E.MPD: Our high-quality molecular patient database as a resource for disease assessment and patient stratification Leveraging patient transcriptomic data to drive target selection and enhance translatability. • Differential expression analysis of identified Treg targets in I&I molecular patient datasets supports candidate prioritization for downstream validation and potential hit identification in modality-relevant campaigns. I. 25 Fresh Blood Single CellRNAseq • 19 SjS and 6 SLE profiles generated • 8 profiles from untreated patients • Collection Ongoing III. ~ 550 Whole Blood RNAseq Profiles • 174 SLE + 374 SjS samples so far • 300 Healthy Control profiles • 90+ untreated patients II. High Sensitivity Seer Serum proteomics • 100 SjS and SLE profiles • 200 Healthy Controls • >1000 peptides regulated in SLE and SjS detected Two endotypes of SLE and SjS patients Clustering based on IFNgene signature expression Peptides Changed Between SLE and Healthy Volcano Plot; SLE vs Healthy scRNAseq profiles of SjS patients UMAP clustering Figure 7: Ongoing non-interventional clinical study enabling longitudinal collection of patient samples from individuals with Systemic Lupus Erythematosus (SLE) and Sjögren’s Syndrome (SjS), contributing to Evotec’s molecular patient database. Conducted in collaboration with the Hannover Medical School (MHH) and Prof. Witte.