ABSCI CORPORATION 2024 ALL RIGHTS RESERVED 42ND JP MORGAN HEALTHCARE CONFERENCE
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 2 Disclaimers Forward-Looking Statements Certain statements in this presentation that are not historical facts are considered forward-looking within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, including statements containing the words “will,” “may,” “anticipates,” “plans,” “believes,” “forecast,” “estimates,” “expects,” “predicts,” “advancing,” “aim,” “potential,” and “intends,” or similar expressions. We intend these forward-looking statements, including statements regarding our strategy, estimated speed, cost advantages, improved success rates, and expanded intellectual property opportunities from developing therapeutics leveraging our AI drug creation platform, the effective incorporation of our technology in drug design and discovery to accelerate drug development and increase probability of success, advancements toward in silico drug design and creation, research and technology development collaboration efforts, including growing partnership momentum for 2024, potential total dollar value of, and milestone and royalty payments due under, our collaboration agreements, projected costs, prospects, plans and objectives of management, to be covered by the safe harbor provisions for forward-looking statements contained in Section 27A of the Securities Act and Section 21E of the Securities Exchange Act, and we make this statement for purposes of complying with those safe harbor provisions. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies, and prospects, which are based on the information currently available to us and on assumptions we have made. We can give no assurance that the plans, intentions, expectations, or strategies will be attained or achieved, and, furthermore, actual results may differ materially from those described in the forward-looking statements and will be affected by a variety of risks and factors that are beyond our control, including, without limitation, risks and uncertainties relating to the development of our technology, our ability to secure milestone payments and royalties, our ability to effectively conduct research, drug discovery and development activities with respect to our internal programs and to collaborate with our partners or potential partners with respect to their research, drug discovery and development activities, and our dependence on third parties to support our internal development programs, including for the manufacture and supply of preclinical and clinical supplies of our product candidates or components thereof; along with those risks set forth in our most recent periodic report filed with the U.S. Securities and Exchange Commission, as well as discussions of potential risks, uncertainties, and other important factors in our subsequent filings with the U.S. Securities and Exchange Commission. Except as required by law, we assume no obligation to update publicly any forward- looking statements, whether as a result of new information, future events, or otherwise. Market and Statistical Information This presentation also contains estimates and other statistical data made by independent parties and by us relating to market size and growth and other industry data. These data involve a number of assumptions and limitations, and you are cautioned not to give undue weight to such estimates. We have not independently verified the data generated by independent parties and cannot guarantee their accuracy or completeness. Trademark usage This presentation/document/webpage contains references to our trademarks and service marks and to those belonging to third parties. Absci®, theAbsci logo mark ( ), SoluPro®, Bionic SoluPro®, and SoluPure® are Absci registered trademarks with the U.S. Patent and Trademark Office. We also use various other trademarks, service marks and trade names in our business, including the the Absci AI logo mark ( ), the Unlimit with us mark ( ), the unlimit symbol ( ), Bionic protein ™, Bionic Enzyme ™, Bionic Antibody™, Denovium ™, Denovium Engine ™, Drug Creation ™, Integrated Drug Creation™, HiPrBind™, HiPrBind Assay™, Translating Ideas into Drugs™, Translating Ideas into Impact™, We Translate Ideas into Drugs™, Creating drugs at the speed of Ai™, Better biologics for patients, faster™, Breakthrough therapeutics at the click of a button, for everyone™, and We Translate Ideas into Impact™. All other trademarks, service marks or trade names referred to in this presentation/document/webpage are the property of their respective owners. Solely for convenience, the trademarks and trade names in this presentation/document/webpage may be referred to with or without the trademark symbols, but references which omit the symbols should not be construed as any indicator that their respective owners will not assert, to the fullest extent under applicable law, their rights thereto.
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 3 R E C E N T S U C C E S S E S N E W P H A R M A P A R T N E R S H I P S • “Astrazeneca Types up $247m AI-enabled Oncology Antibody Design Pact, Joining Absci’s list of Pharma Allies” – Fierce Pharma • “Skin in the Game: Absci Partners with Almirall on Up-to-$650M Dermatology AI Collaboration” –GEN News 1 0 N E W A C T I V E P R O G R A M S I N T E R N A L A S S E T P O R T F O L I O • Achieved guidance for 2023 with growing partnership momentum for 2024 • Internal Asset Portfolio focused on cytokine biology • Lead asset ABS-101, an AI-designed TL1A antibody product candidate Absci is a Data-First Generative AI Drug Creation Company Our Integrated AI & Wet Lab Platform Aims to Engineer Better Biologics Faster at Lower Cost with Design-in Functionality and Best-in- Class Properties
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 4 Integrated Wet-Lab Dry-Lab Drug CreationTM Platform Proprietary wet-lab assays generate massive quantities of high-quality data for generative AI model training Advanced generative AI models used to “create” antibodies and next-gen biologics Scalable wet-lab infrastructure capable of validating millions of unique AI-generated designs a week
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 5 D A T A T O T R A I N SOLUPRO™ CELL LINE ABSCI’S ACE ASSAY™ PROPRIETARY DATA SETS & ASSAYS PUBLIC DATA SETS Proprietary Wet-lab Technologies Generate High-quality Data at Scale Absci’s AI capable of creating billions of antibody designs for our proprietary models and ACE Assay™ technology to subsequently screen millions of ranked antibody sequences in weeks.
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 6 A I T O C R E A T E Target Antigen Structure AI designed antibodies INPUT OUTPUT AI Models Generative AI models utilizing latest architectural innovations to access a massive ~20^55 sequence search space to design antibody-antigen complex structures and sequences in silico Advanced generative AI models to “create” biologics in silico
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 7 F U N C T I O N A L I T Y • Binding Affinity • Specificity to target(s) • Potency • FcRn Recycling • Self association • Hydrophobicity • Solubility • Stability (multiple conditions) D E V E L O P A B I L I T Y W E T L A B T O V A L I D A T E Wet-lab Capable of Validating Millions of AI-Generated Designs in a Week 77,000 SqFt+ Wet-Lab to generate scalable data and validate AI-generated designs in rapid iterative 6-week cycles
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 8 Leveraging AI Throughout the End-to-End Drug Discovery Process I N T E G R A T E D A I W E T - L A B P L A T F O R M T A R G E T D I S C O V E R Y W I T H N O V E L A P P R O A C H E S Reverse Immunology for target discovery A I - G U I D E D L E A D O P T I M I Z A T I O N Multi-parameteric optimized antibodies A I - G U I D E D A N T I B O D Y D R U G C R E A T I O N De novo antibodies designed by AI
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 9 Platform Enables the Potential to Deliver Differentiated Biologics, Faster at Lower Cost V A L U E D R I V E R S ENABLING FIRST-IN-CLASS A C C E S S N O V E L D I S E A S E B I O L O G Y Ability to address elusive drug targets, e.g. GPCRs, Ion Channels ENABLING BEST IN CLASS & HIGHER PROGRAM NPVS I N C R E A S E D P R O B A B I L I T Y O F S U C C E S S Superior Drug Attributes and Multidimensional optimization creates higher quality biologics ENHANCED IP PROTECTION E X P A N D E D I N T E L L E C T U A L P R O P E R T Y S P A C E Generates broader IP for First-in-Class therapies and finds new IP for Best-in-Class therapies FASTER TIME TO IND R E D U C E D T I M E & C O S T T O C L I N I C 2 years and $14-16M from Target to IND; significant reduction compared to industry estimates
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 10 Over $900M + Royalties of Potential Deal Value Signed in the Last 2 Months R E C E N T P A R T N E R S H I P S “Skin in the Game: Absci Partners with Almirall on up- to-$650 Dermatology AI Collaboration” R&D CLINICAL COMMERCIAL ROYALTIES I L L U S T R A T I V E E C O N O M I C S T R U C T U R E O F A S U C C E S S F U L D R U G D I S C O V E R Y P A R T N E R S H I P UPFRONT & RESEARCH FUNDING CLINICAL MILESTONES COMMERCIAL MILESTONES & ROYALTIES -GEN News “Astrazeneca Types up $247m AI-enabled Oncology Antibody Design Pact, Joining Absci’s list of Pharma Allies” -Fierce Pharma D E C 0 4 , 2 0 2 3 N O V 1 4 , 2 0 2 3
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 11 P A R T N E R S H I P S A I D R U G D I S C O V E R Y C O L L A B O R A T I O N S I N T E R N A L A S S E T P I P E L I N E C O L L A B O R A T I O N S D A T A & C O M P U T E C O L L A B O R A T I O N S 1 As of December 31, 2023 Trademarks, service marks or trade names referred to herein are the intellectual property of their respective owners. Use of this IP does not imply affiliation, endorsement or sponsorship of any kind 3 Internal Programs with Potential Best-in -Class or First-in - Class Profile Driving Growth Through Industry-Leading Collaborations including 16 Active Programs1 and 3 Internal Programs
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 12 Internal Pipeline of Potential First-in-Class and Best-in-Class Assets S E L E C T P I P E L I N E H I G H L I G H T S POTENTIAL “BEST-IN-CLASS” POTENTIAL “FIRST-IN-CLASS” DERMATOLOGY / UNDISCLOSED INFL. BOWEL DISEASE / TL1A IMMUNO-ONCOLOGY / UNDISCLOSED A B S - 2 0 1 A B S - 3 0 1 A B S - 1 0 1 T A R G E T V A L L E A D C A N D I D A T E I N D - E N A B L I N G T H E R A P E U T I C A R E A / T A R G E T IND Focus on cytokine biology - first frontier of AI-driven disruption
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 13 Inflammation Fibrosis Clinically Validated Mechanism of Action in Large Underserved Market A B S - 1 0 1 T L 1 A D A T A H I G H L I G H T S T L 1 A : D R 3 S I G N A L I N G C L I N I C A L L Y S H O W N T O I N D U C E P R O - I N F L A M M A T O R Y R E S P O N S E S 1 P O T E N T I A L R E L E V A N C E I N W I D E R A N G E O F A U T O I M M U N E I N D I C A T I O N S DC MΦ Membrane TL1ADR3 T-Cell Signaling Signaling DR3 Soluble TL1A 2 Wang 2023 http://dx.doi.org/10.1136/bmjopen-2022-065186 3 Dahlhamer, James M., et al. "Prevalence of inflammatory bowel disease among adults aged≥ 18 years—United States, 2015." Morbidity and mortality weekly report 65.42 (2016): 1166-1169. 4 Evaluate Pharma Oct 2023. 1 Adapted from Takedatsu 2008 doi: 10.1053/j.gastro.2008.04.037 Significant market opportunities beyond Inflammatory Bowel Disease $22B+ Global Market4 $4.5B for TL1A 0.8- 3M U.S. Inflammatory Bowel Disease Prevalence3 5M Global Inflammatory Bowel Disease (IBD) Prevalence2
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 14 Potential Best-in-Class TL1A mAb Designed using Generative AI A B S - 1 0 1 T L 1 A D A T A H I G H L I G H T S AI-designed TL1A program designed to achieve superior therapeutic properties over clinical competitors D E N O V O A I - D E S I G N E D A N D A I - O P T I M I Z E D S U P E R I O R P R E - C L I N I C A L P R O F I L E A N D P O T E N T I A L F O R S U P E R I O R C L I N I C A L P R O F I L E D I F F E R E N T I A T E D I N T E L L E C T U A L P R O P E R T Y • High Affinity & Potency • Extended Half life & Longer Dosing Intervals • Q8W to once quarterly • Sub-Q Dosing • Low immunogenicity • High bioavailability • Favorable Developability • Target to promising candidates in just over 1 year
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 15 AI Platform Designed Advanced Leads with High Affinity and Superior Potency A B S - 1 0 1 T L 1 A D A T A H I G H L I G H T S H I G H A F F I N I T Y m A B s W I T H P R E S E R V E D C R O S S - R E A C T I V I T Y A I - O P T I M I Z E D L O W p M A F F I N I T Y T R A N S L A T E S T O S U P E R I O R O R E Q U I V A L E N T P O T E N C Y #Estimated performance of a putative clinical competitor molecule generated for in house comparison. MK-7240# RVT-3101# 0.06 0.09 0.12 0.15 0.03 In cr ea si ng a ff in ity ABS-101-AABS-101-B ABS-101-C 0.03 Cyno TL1A KD (nM) H um an T L1 A K D (n M ) In cr ea si ng p ot en cy IC 50 ( nM ) 0 2 4 6 8 10 12 AFFINITY BY SURFACE PLASMON RESONANCE (SPR) APOPTOSIS INHIBITION ASSAY IN TF-1 CELLS
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 16 AI Platform Designed Advanced Leads with Extended Half-life: Supporting Potential for Significantly Improved Dosing Intervals A B S - 1 0 1 T L 1 A D A T A H I G H L I G H T S E X T E N D E D H A L F - L I F E I N V I T R O C O M P A R E D T O C L I N I C A L C O M P E T I T O R S INCREASED RECYCLING OF ABS-101 LEADS IN CELLULAR FcRn RECYCLING ASSAY1 IMPROVED PK PROFILE FOR ABS-101-B IN PK STUDY Tg32 MOUSE MODEL, SINGLE DOSE I.V.2 P R E L I M I N A R Y I N V I V O P K D A T A S H O W S P O T E N T I A L F O R E X T E N D E D H A L F - L I F E 1 Cell-based FcRn recycling assay in HMEC-1 cells. Grevys 2018 2 Homozygous hFcRn Tg32 mouse model, single dose i.v. * Initial mouse PK using surrogate molecule (backbone differences from ABS-101-B). Study data pending for final IgG1 mAb. #Estimated performance of a putative clinical competitor molecule generated for in house comparison 10 20 Re cy cl ed m A b co nc en tr at io n (n M ) 0 Se ru m c on ce nt ra tio n (n g/ m l) Time (Days) RVT-3101 ABS-101-B* 0 10 20 30 40 50 102 103 104 105 106 PARAMETERS ABS-101-B* RVT-3101# t1/2 (d) 12.4 6.8 CL (mL/d/kg) 5.83 12.8 Vss (mL/kg) 98.6 109 AUC0-∞ (µg.d/mL) 1710 784 Increasing recycling
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 17 AI Platform Designed Leads Span Diverse Set of Epitopes Leading to IP Differentiation A B S - 1 0 1 T L 1 A D A T A H I G H L I G H T S MK-7240 # RVT-3101 # Epitope bins* on TL1A * Epitope binning by BLI competition experiment # Estimated performance of clinical competitor reagent generated for comparison ABS-101 binds a unique epitope on TL1A, differentiating ABS-101 from clinical competitors Absci AI-optimized leads span multiple epitopesABS-101-A ABS-101-B ABS-101-C
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 18 A T T R I B U T E A B S - 1 0 1 P R O G R A M * M E R C K ( P R O M E T H E U S ) M K - 7 2 4 0 R O C H E ( R O I V A N T ) R V T - 3 1 0 1 S A N O F I ( T E V A ) T E V - 4 8 5 7 4 Low Immunogenicity** 1 1,5 - High Bioavailability 1 1, 4 - Sub-Q autoinjector 2 3 Q8W to once quarterly dosing 1, 3 1, 3 3 * Projected ABS-101 attributes derived from in silico and in vitro metrics and modeled exposure with ½-life extension ** Low score by 2 in silico immunogenicity metrics and low results in ex vivo testing AI Platform Designed ABS-101 Aims for Optimal Therapeutic Profile A B S - 1 0 1 T L 1 A D A T A H I G H L I G H T S 1 Based on Phase 2 data 2 Expected commercial form factor 3 Once monthly dosing regimen 4 45% BA at 100mg/mL based on Ph2 Data 5 Danase et al 2021 (Pfizer Phase 2 data) reports 41 participants out of 50 participants (82%) developing ADA, and 5 (10%) of these developed neutralizing ADA
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 19 AI-Designed Advanced Leads High Affinity High Potency Long Half-Life Favorable Manufacturability T O D A Y I N I T I A T I N G F E B ‘ 2 4 1 Q 2 5 IND-enabling studies to evaluate • Sub-Q formulation • Favorable PK with long half-life • Low ADA • High Bioavailability • High Tolerability (low tox) Initiating Phase 1 Trial 1 H 2 5 Investigational New Drug (IND) Submission A B S - 1 0 1 T L 1 A D A T A H I G H L I G H T S Pro jected T im eline to Po tential Best- in- C lass M o lecule
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 20 ~ 1 6 0 77,000+ Square Feet ~$450M Unlimiters with deep experience in AI, drug discovery, immunology, and synthetic biology State-of-the-art drug creation and wet lab space in Vancouver WA, Absci AI Research (AAIR) lab in NYC, and the Innovation Centre in Zug Switzerland Capital raised to date Biologics drug discovery expertise from: Leading AI team with expertise from: 16 Active Programs* Absci’s talent and Infrastructure for Better Biologics Faster, at Lower Cost Trademarks, service marks or trade names referred to herein are the intellectual property of their respective owners. Use of this IP does not imply affiliation, endorsement or sponsorship of any kind W E L L - P O S I T I O N E D T O D E L I V E R Named Internal Asset Programs*3 * As of December 31, 2023
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 21 KAREN MCGINNIS, CPA Lead Independent Director Former CAO, Illumina AMRIT NAGPAL Managing Director, Redmile Group JOSEPH SIROSH, PHD Former CTO, Compass VP, Amazon & Microsoft DAN RABINOVITSJ Vice President Connectivity, Meta FRANS VAN HOUTEN Former CEO, Royal Phillips B O A R D O F D I R E C T O R S SIR MENE PANGALOS, PHD Former EVP R&D AstraZeneca Leadership Team of Innovators Across AI and Biotech to Transform Drug Discovery W O R L D - C L A S S T E A M Trademarks, service marks or trade names referred to herein are the intellectual property of their respective owners. Use of this IP does not imply affiliation, endorsement or sponsorship of any kind L E A D E R S H I P T E A M SEAN MCCLAIN Founder, CEO & Director ANDREAS BUSCH, PHD Chief Innovation Officer ZACH JONASSON, PHD Chief Financial Officer, Chief Business Officer AMARO TAYLOR-WEINER, PHD SVP, Chief AI Officer KARIN WIERINCK Chief People Officer CHRISTIAN STEGMANN, PHD SVP, Drug Creation CHRISTINE LEMKE, DVM SVP, Portfolio & Growth Strategy JENS PLASSMEIER, PHD SVP, Biologics Discovery Technologies PENELOPE Chief Morale Officer JACK GOLD Chief Marketing Officer
C O P Y R I G H T © 2 0 2 4 A B S C I C O R P O R A T I O N . A L L R I G H T S R E S E R V E D . 22 IND submission for ABS-101 in 1Q25 in-vivo validation studies for ABS-301, potential ‘first- in-class’ immuno-oncology asset Development Candidate selection for ABS-201; potential ‘best-in-class’ dermatology asset IND-enabling studies initiating for ABS-101 (TL1A) Feb ‘24 Platform validated through industry- leading partnerships, most recently with AstraZeneca and Almirall U P C O M I N G C A T A L Y T S & C O N T I N U E D P A R T N E R S H I P M O M E N T U M ‘Data to Train’, ‘AI to Create’, and ‘Wet Lab to Validate’ in rapid 6-week cycles Internal pipeline of potentially ‘best- in-class’ (TL1A) and ‘first-in-class’ asset programs Better Biologics Faster and at Lower Cost