Valuation: Exscientia plc

Market Cap 500M 680M 583M 545M 940M 65.01B 955M 6.43B 2.52B 32.6B 2.55B 2.5B 108B P/E 2022
-4.55x
P/E 2023 -4.28x
Enterprise Value 156M 212M 182M 170M 293M 20.25B 298M 2B 784M 10.16B 796M 778M 33.58B 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
7.91
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%-.--%-.--%-24.02% 633M
+2.37%+2.30%+3.39%+22.74% 48.63B
-0.62%+4.58%+487.47%+624.71% 46.3B
+2.09%+4.96%+20.59%+95.21% 41.97B
+3.85%+3.13%+29.60%+16.50% 39.51B
-0.72%-3.91%+17.87%+47.98% 31.75B
+3.04%+1.89%+31.62%+143.62% 16.48B
+4.33%+1.63% - - 16.34B
+1.44%+1.52%+4.22%+31.00% 14B
+3.87%+1.98%+82.99%+45.80% 13.33B
Average +2.29%+0.94%+75.31%+111.50% 26.89B
Weighted average by Cap. +1.85%+0.96%+106.97%+156.75%

Financials

2022 2023
Net sales 27.22M 37.04M 31.78M 29.67M 51.19M 3.54B 52.04M 350M 137M 1.78B 139M 136M 5.87B 20.08M 27.32M 23.44M 21.89M 37.76M 2.61B 38.38M 258M 101M 1.31B 103M 100M 4.33B
Net income -119M -162M -139M -129M -223M -15.44B -227M -1.53B -598M -7.74B -607M -593M -25.61B -146M -199M -170M -159M -274M -18.98B -279M -1.88B -735M -9.52B -746M -730M -31.48B
Net Debt -492M -669M -574M -536M -925M -63.98B -940M -6.33B -2.48B -32.09B -2.51B -2.46B -106B -344M -468M -402M -375M -647M -44.76B -658M -4.43B -1.73B -22.45B -1.76B -1.72B -74.22B
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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