Valuation: Exscientia plc

Market Cap 500M 670M 586M 541M 950M 63.93B 966M 6.48B 2.54B 31.48B 2.51B 2.46B 109B P/E 2022
-4.55x
P/E 2023 -4.28x
Enterprise Value 156M 209M 183M 168M 296M 19.92B 301M 2.02B 790M 9.81B 783M 767M 33.91B EV / Sales 2022
1.9x
EV / Sales 2023 14.2x
Free-Float
36.87%
Yield 2022 *
-
Yield 2023 -
3 years 3.8
Extreme 3.8
9.12
5 years 3.8
Extreme 3.8
30.38
10 years 3.8
Extreme 3.8
30.38
Manager TitleAgeSince
Chief Tech/Sci/R&D Officer 61 2024-06-05
Chief Tech/Sci/R&D Officer - 2022-04-30
Chief Tech/Sci/R&D Officer - 2024-04-30
Director TitleAgeSince
Director/Board Member 63 2017-09-27
Director/Board Member 43 2020-04-30
Chairman 61 2024-02-11
Change 5-day change 1-year change 3-year change Capi.($)
+3.20%-.--%-.--%-22.50% 633M
+1.68%+3.55%+4.86%+10.97% 49.42B
+0.72%+1.93%+424.51%+624.25% 40.34B
+2.54%+2.84%+27.06%-3.62% 34.01B
+0.31%+4.16%+23.87%+59.76% 33.56B
-2.09%-0.80%+3.56%+33.56% 26.84B
-0.63%+2.85% - - 17.22B
+0.66%-1.48%+66.05%+127.36% 15.19B
-23.90%-18.84%+55.47%+53.83% 13.96B
+2.59%+0.50%+15.28%+21.25% 13.36B
Average -1.49%+0.74%+68.96%+100.54% 24.45B
Weighted average by Cap. -0.59%+0.89%+93.11%+138.42%

Financials

2022 2023
Net sales 27.22M 36.51M 31.92M 29.45M 51.73M 3.48B 52.59M 353M 138M 1.71B 137M 134M 5.93B 20.08M 26.93M 23.54M 21.72M 38.15M 2.57B 38.79M 260M 102M 1.26B 101M 98.91M 4.37B
Net income -119M -159M -139M -128M -226M -15.19B -229M -1.54B -602M -7.48B -597M -585M -25.85B -146M -196M -171M -158M -277M -18.67B -282M -1.89B -741M -9.19B -734M -719M -31.78B
Net Debt -492M -660M -577M -532M -935M -62.92B -950M -6.37B -2.5B -30.98B -2.47B -2.42B -107B -344M -461M -404M -372M -654M -44.02B -665M -4.46B -1.75B -21.67B -1.73B -1.7B -74.94B
Logo Exscientia plc
Exscientia PLC is a drug design and development company. The Company combines precision design with integrated experimentation to invent and develop drugs. It uses artificial intelligence (AI) in drug discovery to progress AI-designed small molecules into a clinical setting. It uses the patient's tissue data to define optimal profiles for research, improve experimental assessment during design and improve outcomes in a medical setting. It has developed an internal pipeline focused on oncology, while its partnered pipeline extends to various other therapeutic areas. It combines genetic data and global literature in machine learning models to anticipate and confirm disease-target associations. The Company's experimental platform records responses in real patient samples allowing it to generate high-precision views of potential patient response. Its product pipeline consists of GTAEXS617, EXS4318, EXS74539, and EXS73565.
Employees
483
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