Valuation: Exscientia plc

Market Cap 500M 661M 590M 550M 941M 63.97B 950M 6.61B 2.58B 32.51B 2.48B 2.43B 105B P/E 2022
-4.55x
P/E 2023 -4.28x
Enterprise Value 156M 206M 184M 171M 293M 19.93B 296M 2.06B 805M 10.13B 773M 756M 32.57B 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
25.16
10 years 3.8
Extreme 3.8
30.38
Manager TitleAgeSince
Chief Tech/Sci/R&D Officer 61 06/06/2024
Chief Tech/Sci/R&D Officer - 01/05/2022
Chief Tech/Sci/R&D Officer - 01/05/2024
Director TitleAgeSince
Director/Board Member 63 28/09/2017
Director/Board Member 43 01/05/2020
Chairman 61 12/02/2024
Change 5-day change 1-year change 3-year change Capi.($)
+3.20%-.--%-.--%+4.09% 633M
-3.19%-3.19%+44.60%+87.98% 74.68B
-15.86%-16.67%+3.92%+50.90% 58.7B
-2.39%-2.05%+4.29%+31.33% 48.36B
-6.35%-8.63%+293.39%+638.59% 43.05B
+0.30%-0.71%+29.05%+29.74% 42.48B
-3.82%-2.41%-0.27%+102.63% 41.39B
-2.13%+1.07%+7.51%+50.31% 31.29B
-3.35%-4.95%-13.38%-15.78% 23.93B
-1.24%-7.47%-37.90%+309.96% 22.22B
Average -3.47%-2.37%+33.12%+128.97% 38.67B
Weighted average by Cap. -4.83%-1.88%+43.17%+134.88%

Financials

2022 2023
Net sales 27.22M 35.97M 32.12M 29.97M 51.23M 3.48B 51.73M 360M 141M 1.77B 135M 132M 5.69B 20.08M 26.53M 23.69M 22.1M 37.78M 2.57B 38.15M 265M 104M 1.31B 99.62M 97.46M 4.2B
Net income -119M -157M -140M -131M -223M -15.2B -226M -1.57B -614M -7.72B -589M -576M -24.83B -146M -193M -172M -161M -275M -18.68B -277M -1.93B -755M -9.49B -724M -708M -30.53B
Net Debt -492M -650M -580M -542M -926M -62.96B -935M -6.5B -2.54B -31.99B -2.44B -2.39B -103B -344M -455M -406M -379M -648M -44.04B -654M -4.55B -1.78B -22.38B -1.71B -1.67B -71.97B
Projected Income Statement - Annual - Exscientia plc
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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