Valuation: Exscientia plc

Market Cap 500M 675M 583M 545M 940M 64.2B 955M 6.39B 2.51B 32.18B 2.53B 2.48B 106B P/E 2022
-4.55x
P/E 2023 -4.28x
Enterprise Value 156M 210M 182M 170M 293M 20B 298M 1.99B 782M 10.02B 789M 772M 33.14B 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 - 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
Director/Board Member 43 30/04/2020
Chairman 61 11/02/2024
Change 5-day change 1-year change 3-year change Capi.($)
+3.20%-.--%-.--%-34.59% 633M
+0.99%+1.78%+4.07%+16.73% 49.47B
+3.71%+9.40%+486.98%+592.14% 43.61B
+5.60%+10.21%+16.76%+85.72% 39.6B
+2.70%+1.57%+33.39%+8.85% 39.29B
+2.21%+6.75%+21.31%+53.37% 32.43B
+2.23%+4.71% - - 16.84B
+0.97%+2.35%+37.75%+126.84% 16.49B
-0.11%+2.41%+6.24%+18.87% 14.01B
+0.75%+15.04%+78.59%+30.30% 12.77B
Average +2.23%+5.69%+76.12%+99.80% 26.51B
Weighted average by Cap. +2.54%+6.08%+103.99%+140.34%

Financials

2022 2023
Net sales 27.22M 36.74M 31.78M 29.68M 51.2M 3.5B 52.02M 348M 137M 1.75B 138M 135M 5.79B 20.08M 27.1M 23.44M 21.89M 37.77M 2.58B 38.37M 257M 101M 1.29B 102M 99.53M 4.27B
Net income -119M -160M -139M -129M -223M -15.25B -227M -1.52B -596M -7.64B -602M -588M -25.27B -146M -197M -170M -159M -275M -18.75B -279M -1.87B -733M -9.4B -740M -723M -31.06B
Net Debt -492M -664M -574M -536M -925M -63.18B -940M -6.29B -2.47B -31.67B -2.49B -2.44B -105B -344M -464M -402M -375M -647M -44.2B -658M -4.4B -1.73B -22.15B -1.74B -1.71B -73.24B
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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