Slide 1: Decoding Biology To Radically Improve Lives
Decoding Biology To Radically Improve Lives U2 LUL2 So Recursion
Slide 2: Forward-looking statements
This presentation and any accompanying discussion or documents may contain information that includes or is based upon "forward- looking statements" within the meaning of the Securities Litigation Reform Act of 1995. These forward-looking statements are based on our current expectations, estimates an
Slide 3: Recursion is a clinical stage Pharmatech company
Recursion is a clinical stage Pharmatech company Mapping and Navigating biology and chemistry with the goal of bringing better medicines to patients faster and at lower cost via an Internal Pipeline and Partnerships The Leading Pharmatech Mission is to decode biology to radically improve lives >150
Slide 4: Top-20 Pharma vs AI-native drug discovery companies assets
Images adapted from Jayatunga, M., et al. Nature Reviews Drug Discovery 2022. 4 Top-20 Pharma Companies AI-Native Drug Discovery Companies 705 768 708 602 575 641 686 709 519 439 393 333 0 500 1,000 1,500 2,000 2,500 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Discovery / Preclinical
Slide 5: Relationships between key members of five pathways
Well-known primary relationships between key members of five pathways: JAK/STAT | SWI/SNF | TGFβ | RAS | Proteasome All primary relationships found by the Recursion OS between key members of five pathways: JAK/STAT | SWI/SNF | TGFβ | RAS | Proteasome 5
Slide 6: Build, integrate and organize to deploy novel insights
6 build relatable datasets to uncover novel insights integrate diverse technologies to scale novel insights organize aspects of the value chain to deploy novel insights
Slide 7: Real (atoms) and Digital (bits): systems, data, algorithms
Real (atoms) Digital (bits) 1 Profile Systems Capture high-dimensional data to create a digital record of reality (things, places, preferences, etc.) Data Aggregate and organize data to create digital maps of reality Algorithms Navigate digital maps to predict novel relationships, then try them in r
Slide 8: How we build maps of biology and chemistry
How we build maps of biology and chemistry
Slide 9: How we build maps of biology and chemistry
How we build maps of biology and chemistry Enables quality, reliability, repeatability and scale Novel Efficacy and Insights different human cell types small molecule library, we believe this scale is on par with some large pharma companies arrayed CRISPR guides cytokines and soluble factors Diverse
Slide 10: How we navigate maps of biology and chemistry
How we navigate maps of biology and chemistry to potentially drive better programs faster 10
Slide 11: Whole-genome arrayed CRISPR knock-out Map
To the left is a whole-genome arrayed CRISPR knock-out Map generated in primary human endothelial cells Recursion visualizes its Maps in different ways. Below is a Map of thousands of new chemical entities, clustered by chemical similarity and colored by potency, which demonstrated a strong anti-inf
Slide 12: Mitochondrial-related genes cluster together
Many known mitochondrial-related genes cluster together along with a few less well-known genes 12
Slide 13: JAK / STAT pathway clustered by strength of interaction
JAK1 JAK1 The JAK / STAT pathway clustered by strength of interaction, including both similar genes (red) and ‘opposite’ genes (blue) – note that both expected and less well-known genes can serve as novel hypotheses 13
Slide 14: 20S and 26S proteasomes form expected clusters
20S Subunit 26S Subunit The 20S and 26S proteosomes form expected clusters that give confidence in this Map, one of many we have built – however, the most exciting elements of each map are the tens of thousands of unknown and unexplored high- confidence relationships 14
Slide 15: Traditional approach versus map of biology and chemistry
World’s literature reviewed People generate hypotheses Hypotheses validated in low dimensional assays 1. Millions of disparate journal articles and publications 2. Many data cannot be independently replicated 3. Human-selected low dimensional assays prone to confirmation bias 4. Humans prone to conf
Slide 16: Failing faster and earlier to spend less and go faster
Data shown are the averages of all our programs from 2017 through 2021. All industry data adapted from Paul, et al. Nature Reviews Drug Discovery. (2010) 9, 203–214 Screen — Hit ID — Validated Lead — Advanced Candidate — Development Candidate — Industry Recursion Failing faster and earlier to › › sp
Slide 17: Leading indicators of efficiency including scale
Mapping and navigating biology and chemistry has demonstrated leading indicators of efficiency including scale (© CEREBRAL CAVERNOUS MALFORMATION ‘Stage of Development (Cov est 3600) CLINICAL © Spun, aDenowarouspoLYPosts (© newmorigromarosis rE 2 (© GMa cansuiosiposis, (HEKAMENE et. 400) PRECLINICAL
Slide 18: Partnership and pipeline strategy
Internal Pipeline - Rare Genetic Diseases Asset Sales / Licenses / Commercialization Partnership strategy • Partner in large, difficult and/or competitive therapeutic areas • Add knowledge to and improve our growing atlas of biology Internal Pipeline Discovery Partnerships Commercialization, licensi
Slide 19: Illustrative example of potential value inflection points
Program 1 Program 1 Program 1 Program 1 Program 1 Program 1 Program 1 Illustrative example of potential value inflection points Upfront Fee Programs 2 through N Programs 2 through N Programs 2 through N Programs 2 through N Programs 2 through N Collaboration Timeline Programs 2 through N Programs 2
Slide 20: Cerebral Cavernous Malformation (REC-994)
US + EU5 PREVALENCE CAUSE LOF mutations in genes CCM1, CCM2 & CCM3, key for maintaining the structural integrity of the vasculature due to unknown mechanisms PATHOPHYSIOLOGY Vascular malformations of the CNS leading to focal neurological deficits, hemorrhage and other symptoms OUR REASON TO BELIEVE
Slide 21: NF2 meningioma (REC-2282)
US + EU5 INCIDENCE CAUSE LOF mutations in NF2 tumor suppressor gene PATHOPHYSIOLOGY OUR REASON TO BELIEVE Efficacy in Recursion OS, cellular, & animal models; suppression of aberrant ERK, AKT, and S6 pathway activation in a Phase 1 PD Study in NF2 patient tumors KEY ELEMENTS • Targeting familial and
Slide 22: Familial adenomatous polyposis (REC-4881)
US + EU5 PREVALENCE CAUSE Inactivating mutations in the tumor suppressor gene APC PATHOPHYSIOLOGY Polyps throughout the GI tract with extremely high risk of malignant transformation OUR REASON TO BELIEVE Efficacy in the Recursion OS shows that specific MEK 1/2 inhibitors had an effect in context of
Slide 23: C. difficile colitis (REC-3964)
US + EU5 INCIDENCE CAUSE Release of C. difficile toxins by colonizing bacterium causes degradation of colon cell junction, toxin transit to bloodstream, and morbidity to host PATHOPHYSIOLOGY Highly recurrent infectious disease with severe diarrhea, colitis, and risk of toxic megacolon, sepsis, and d
Slide 24: HRD-negative ovarian cancer (REC-65029)
Gene A CDK12 2.5μM 1.0μM REC-65029 0.1μM 0.25μM REC-65029 • Goal: Identify potential first-in-class NCE with novel MOA capable of potentially treating HRD-negative ovarian cancer • Phenomap insight: Inhibition of target Gene A (for example, with REC-65029) may mimic inhibition of CDK12 while mitigat
Slide 25: Cancer immunotherapy target (REC-648918)
Efficacy demonstrated in CT26 checkpoint resistance (left) mouse model; complete response (CR) mice show minimal tumor growth when rechallenged (middle left). Peripheral IL-6 remain unchanged (middle right) while intertumoral IFNγ increases EMT6 Gene B Gene B REC- 648918 REC-648918 BIRC2 Gene A Gene
Slide 26: STK11 tumor-intrinsic immune resistance (REC-64151)
• Goal: Identify novel compounds capable of re-sensitizing tumors to checkpoint therapy in STK11 mutant cancers • Phenomap insight: Novel class of compounds (REC-64151) inferred to rescue loss of STK11 • Result: REC-64151 restores anti-PD1 (aPD1) response of STK11 mutant CT26 tumors (Fig. A, B) and
Slide 27: MYC: platform to identify small molecule inhibitors
-2 -1 0 1 2 0 50 100 % P ro lif er at io n In hi bi tio n PC-12 MSTO-211H MV-4-11 HL-60 REC-142221 Conc. (Log, uM) -2 -1 0 1 2 0 50 100 % P ro lif er at io n In hi bi tio n REC-136467 Conc. (Log, uM) c-Myc Independent Cell Line: PC-12 c-Myc Dependent Cell Lines: MSTO-211H MV-4-11 HL-60 MYC: Platform
Slide 28: Committed to ESG Excellence
Advanced degreesEmployees Team Members 450+ 42% ESG Highlights Data shown reflective of Q2 2022 and Recursion’s 2022 ESG report Inaugural ESG report in 2022 – reporting on Healthcare and Technology Metrics 100% of electricity powering our Biohive-1 supercomputer comes from renewable sources 45%
Slide 29: Recursion OS build: today to intermediate-term
Enables quality, reliability, repeatability and scale Recursion OS Continued digital chemistry and predictive ADMET OS build Clinical Predictions Near-TermToday Intermediate-Term 29
Slide 30: Recent milestones achieved and upcoming milestones
• Expanded Bayer collaboration to use mapping and navigating techniques to explore fibrotic diseases • Announced transformational collaboration with Roche-Genentech focused predominantly in neuroscience • Initiated Phase 2 clinical trial evaluating REC-994 for the potential treatment of CCM • Initia
Slide 31: Appendix
Appendix 31
Slide 32: Executive Team and Board of Directors
Board of Directors TINA LARSON President & COO Executive Team DEAN LI, MD/PHD Recursion Co-Founder, President of Merck Research Labs ZACHARY BOGUE, JD Co-Founder & Partner, Data Collective ROB HERSHBERG, MD/PHD Co-Founder/CEO/Chair of HilleVax, Former EVP CSO & BD at Celgene BLAKE BORGESON, PHD Recu
Slide 33: Recursion is a leading pharmatech company
Recursion is a leading pharmatech company TOP TECH ENABLED DRUG DISCOVERY (TEDD) COMPANIES: FROST & SULLIVAN ANALYSIS Mature internal pipeline, large strategic partnerships, advanced computational resources = Abcellera@ © @ Recursion @ @exscientia Schrodinger @ @ Relay Therapeutics @ Valo Health Com
Slide 34: Growth in inputs and outputs
• Growth in capabilities, proprietary data, programs, and partnerships • Increasing business opportunities • Reducing binary risks We are a biotechnology company scaling more like a technology company, as demonstrated by our growth in inputs (experiments) and growth in outputs (data, biological and