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Valuation: Exscientia plc

Market Cap 500M 661M 576M 534M 936M 62.37B 943M 6.34B 2.45B 30.71B 2.48B 2.43B 107B P/E 2022
-4.55x
P/E 2023 -4.28x
Enterprise Value 156M 206M 180M 166M 292M 19.43B 294M 1.97B 765M 9.57B 773M 757M 33.24B 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 - 30/04/2022
Chief Tech/Sci/R&D Officer 61 05/06/2024
Chief Tech/Sci/R&D Officer - 30/04/2024
Director TitleAgeSince
Director/Board Member 63 27/09/2017
Chairman 61 11/02/2024
Director/Board Member 43 30/04/2020
Change 5-day change 1-year change 3-year change Capi.($)
+3.20%-.--%-.--%-32.31% 633M
+1.44%+1.71%-10.63%-9.16% 43.13B
+3.31%+5.93%+308.19%+562.02% 34.65B
+2.84%+2.14%+6.87%+34.93% 30.03B
-1.70%-7.54%+8.51%-22.34% 28B
-1.90%-1.56%+11.62%+19.80% 24.45B
-0.14%+5.86% - - 14.34B
+0.68%-1.53%+52.04%+107.47% 13.14B
-0.57%-2.43%+5.18%+4.20% 12.53B
-0.26%+1.15%+100.27%+80.69% 12.25B
Average +0.69%+0.66%+53.56%+82.81% 21.32B
Weighted average by Cap. +0.78%+1.27%+65.02%+112.76%

Financials

2022 2023
Net sales 27.22M 36.02M 31.4M 29.06M 50.99M 3.4B 51.37M 345M 134M 1.67B 135M 132M 5.81B 20.08M 26.57M 23.16M 21.44M 37.61M 2.51B 37.89M 255M 98.6M 1.23B 99.63M 97.58M 4.29B
Net income -119M -157M -137M -127M -222M -14.82B -224M -1.51B -583M -7.3B -589M -577M -25.34B -146M -193M -168M -156M -273M -18.21B -275M -1.85B -717M -8.97B -724M -709M -31.16B
Net Debt -492M -651M -567M -525M -921M -61.39B -928M -6.24B -2.42B -30.23B -2.44B -2.39B -105B -344M -455M -397M -367M -645M -42.94B -649M -4.36B -1.69B -21.14B -1.71B -1.67B -73.46B
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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