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Valuation: Exscientia plc

Market Cap 50Cr 66Cr 58Cr 53Cr 94Cr 6.24TCr 94Cr 633.42Cr 245.49Cr 3.07TCr 248.2Cr 242.88Cr 11TCr P/E 2022
-4.55x
P/E 2023 -4.28x
Enterprise Value 16Cr 21Cr 18Cr 17Cr 29Cr 1.94TCr 29Cr 197.33Cr 76Cr 956.67Cr 77Cr 76Cr 3.32TCr 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 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%-.--%-.--%-32.31% 63Cr
+1.44%+1.71%-10.63%-9.16% 4.27TCr
+3.31%+5.93%+308.19%+562.02% 3.47TCr
+2.84%+2.14%+6.87%+34.93% 3TCr
-1.70%-7.54%+8.51%-22.34% 2.8TCr
-1.90%-1.56%+11.62%+19.80% 2.48TCr
-0.14%+5.86% - - 1.43TCr
+0.68%-1.53%+52.04%+107.47% 1.31TCr
-0.57%-2.43%+5.18%+4.20% 1.26TCr
-0.26%+1.15%+100.27%+80.69% 1.22TCr
Average +0.69%+0.48%+53.56%+82.81% 2.13TCr
Weighted average by Cap. +0.78%+0.90%+65.03%+112.78%

Financials

2022 2023
Net sales 2.72Cr 3.6Cr 3.14Cr 2.91Cr 5.11Cr 339.8Cr 5.14Cr 34Cr 13Cr 167.26Cr 14Cr 13Cr 580.76Cr 2.01Cr 2.66Cr 2.32Cr 2.14Cr 3.77Cr 250.63Cr 3.79Cr 25Cr 9.86Cr 123.36Cr 9.97Cr 9.76Cr 428.35Cr
Net income -12Cr -16Cr -14Cr -13Cr -22Cr -1.48TCr -22Cr -150.46Cr -58Cr -729.45Cr -59Cr -58Cr -2.53TCr -15Cr -19Cr -17Cr -16Cr -27Cr -1.82TCr -28Cr -184.97Cr -72Cr -896.78Cr -72Cr -71Cr -3.11TCr
Net Debt -49Cr -65Cr -57Cr -53Cr -92Cr -6.14TCr -93Cr -623.39Cr -241.6Cr -3.02TCr -244.27Cr -239.03Cr -10TCr -34Cr -46Cr -40Cr -37Cr -65Cr -4.3TCr -65Cr -436.1Cr -169.01Cr -2.11TCr -170.88Cr -167.21Cr -7.34TCr
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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