Exscientia PLC
NASDAQ:EXAI
Decide at what price you'd be comfortable buying and we'll help you stay ready.
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P/E
Price to Earnings (P/E) ratio shows how much investors pay for each dollar of a company`s earnings. It`s calculated by dividing the company`s market value by its total earnings.
Price to Earnings (P/E) ratio shows how much investors pay for each dollar of a company`s earnings. It`s calculated by dividing the company`s market value by its total earnings.
Valuation Scenarios
If P/E returns to its Industry Average (0.8), the stock would be worth $-1.06 (122% downside from current price).
| Scenario | P/E Value | Implied Price | Upside/Downside |
|---|---|---|---|
| Current Multiple | -3.5 | $4.84 |
0%
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| Industry Average | 0.8 | $-1.06 |
-122%
|
| Country Average | 0.2 | $-0.29 |
-106%
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Forward P/E
Today’s price vs future net income
Peer Comparison
| Market Cap | P/E | ||||
|---|---|---|---|---|---|
| UK |
|
Exscientia PLC
NASDAQ:EXAI
|
608.4m USD | -3.5 | |
| FR |
|
Pharnext SCA
OTC:PNEXF
|
6T USD | -160 127.7 | |
| US |
|
Abbvie Inc
NYSE:ABBV
|
360.5B USD | 86.1 | |
| US |
|
Amgen Inc
NASDAQ:AMGN
|
182.2B USD | 23.6 | |
| US |
|
Gilead Sciences Inc
NASDAQ:GILD
|
159.9B USD | 18.8 | |
| US |
E
|
Epizyme Inc
F:EPE
|
94.1B EUR | -533.6 | |
| US |
|
Vertex Pharmaceuticals Inc
NASDAQ:VRTX
|
107.5B USD | 27.2 | |
| US |
|
Regeneron Pharmaceuticals Inc
NASDAQ:REGN
|
72.5B USD | 16.1 | |
| NL |
|
argenx SE
XBRU:ARGX
|
40.6B EUR | 36.7 | |
| US |
S
|
Seagen Inc
F:SGT
|
39.3B EUR | -61.8 | |
| AU |
|
CSL Ltd
ASX:CSL
|
60.6B AUD | 29.4 |
Market Distribution
| Min | 0 |
| 30th Percentile | 0.1 |
| Median | 0.2 |
| 70th Percentile | 0.3 |
| Max | 828.3 |
Other Multiples
Exscientia PLC
Glance View
Exscientia Plc operates as an AI-driven pharmatech company which is engaged in designing and developing patient-based drugs. The company is headquartered in Oxford, Oxfordshire and currently employs 208 full-time employees. The company went IPO on 2021-10-01. The firm's focus is on the discovery, design and development of small molecule drug candidates. The firm has built a complete end-to-end solution of artificial intelligence (AI), and experimental technologies for target identification, drug candidate design, translational models and patient selection. Its AI process is comprised of the four elements: Precision Target, Precision Design, Precision Experiment and Precision Medicine. Its AI-design includes a range of deep learning and machine learning algorithms, generative methods, active learning and natural language processing. These methods are used to guide target selection, to design the precise molecular architecture of potential drug molecules and to analyze patient tissues to prioritize the molecules. The firm's lead drug candidate, EXS21546, is in early stage of development.
