AI in Pharma: Discovery is focused on exploring the applications of AI-based technology in drug discovery and development, specifically how AI, ML, NLP, data science, and generative deep learning models can optimize the pharmaceutical and biotechnology industries.

AI in Pharma: Discovery

Bristol-Myers Squibb Company discovers, develops, licenses, manufactures, and markets biopharmaceutical products worldwide. It offers products for hematology, oncology, cardiovascular, immunology, fibrotic, neuroscience, and covid-19 diseases. The company's products include Revlimid, an oral immunomodulatory drug for the treatment of multiple myeloma; Eliquis, an oral inhibitor for reduction in risk of stroke/systemic embolism in NVAF, and for the treatment of DVT/PE; Opdivo for anti-cancer indications; Pomalyst/Imnovid indicated for patients with multiple myeloma; and Orencia for adult patients with active RA and psoriatic arthritis. It also provides Sprycel for the treatment of Philadelphia chromosome-positive chronic myeloid leukemia; Yervoy for the treatment of patients with unresectable or metastatic melanoma; Abraxane, a protein-bound chemotherapy product; Reblozyl for the treatment of anemia in adult patients with beta thalassemia; and Empliciti for the treatment of multiple myeloma. In addition, the company offers Zeposia to treat relapsing forms of multiple sclerosis; Breyanzi, a CD19-directed genetically modified autologous T cell immunotherapy for the treatment of adult patients with relapsed or refractory large B-cell lymphoma; Inrebic, an oral kinase inhibitor indicated for the treatment of adult patients with myelofibrosis; and Onureg for the treatment of adult patients with AML. It sells products to wholesalers, distributors, pharmacies, retailers, hospitals, clinics, and government agencies. The company was formerly known as Bristol-Myers Company. The company was founded in 1887 and is headquartered in New York, New York.

E. R. Squibb

John Ripley Myers

William McLaren Bristol

Bristol-Myers Squibb Company

Deep Genomics develops an AI platform for RNA biology to identify novel targets and evaluate therapeutic candidates for genetic conditions.

Deep Genomics

Enlitic provides data analytics solutions for healthcare, specializing in improving medical imaging data quality and workflow efficiencies through artificial intelligence.

Enlitic

AI in Pharma: Discovery is an event focused on exploring advancements in artificial intelligence within the pharmaceutical and biotechnology industry.

Metric
Company Name	AI in Pharma: Discovery	Bristol-Myers Squibb Company	Deep Genomics	Enlitic
Symbol		BMY
MSH ID	COM:AIINPHARMA-DISCOVERY	COM:BMS	COM:DEEPGENOMICS	COM:ENLITIC
Market	PRIVATE	STOCKS	PRIVATE	PRIVATE
Sector	Healthcare & Health Services	Healthcare	Healthcare & Health Services	Healthcare & Health Services
Industry	Pharmaceuticals	Drug Manufacturers - General	Biotechnology	Health Technology
Country	US	US	CA	US
Stage
Employee Count		34.10K	107
Website	aiinpharma-discovery.com	bms.com	deepgenomics.com	enlitic.com
LinkedIn			deep-genomics
Founders

Metric
Market Cap		83.35B
Enterprise Value
Monthly Web Traffic
Web Traffic Growth
Valuation
Raised Capital

Metric
Revenue		45.01B
Revenue (LTM)
Revenue (NTM)
Gross Profit		34.31B
EBITDA		19.18B
Operating Income		17.24B
Net Income		8.03B
EPS		3.88
Diluted EPS		3.86
Revenue 2022
Revenue 2023
Revenue 2024
Revenue 2025
Revenue 2026

Metric
Revenue Growth (LTM)
Revenue Growth (NTM)
Gross Profit Growth (LTM)
EBITDA Growth (LTM)
Net Income Growth (LTM)
14-Day Growth Score
28-Day Growth Score
90-Day Growth Score
365-Day Growth Score

Metric
Gross Profit Margin		0.76
Operating Profit Margin		0.31
EBITDA Margin		0.43
Net Profit Margin		0.18
Return on Equity		0.26
Return on Assets		0.08
Return on Capital Employed		0.19

AIIN

COM:AIINPHARMA-DISCOVERY

AI in Pharma: Discovery

Company Overview

Market Metrics

Financial Performance

Growth Metrics

Profitability Ratios

Valuation Multiples

Operational Metrics

Cash Flow Metrics

Balance Sheet Metrics

Efficiency Metrics

Metric
P/E Ratio		11.94
P/B Ratio		3.41
Revenue Multiple (LTM)
Revenue Multiple (NTM)
EBITDA Multiple (LTM)
EBITDA Multiple (NTM)
Price to Sales Ratio		2.36
EV Multiple		4.18

Metric
Days Sales Outstanding		127.10
Days Payables Outstanding		97.40
Days Inventory Outstanding		98.52
Operating Cycle		214.66
Cash Conversion Cycle		103.41
Asset Turnover		0.49

Metric
Operating Cash Flow		13.86B
Free Cash Flow		12.65B
Cash Flow to Debt		0.33
Operating Cash Flow/Sales		0.31
Free Cash Flow Yield		0.12

Metric
Cash & Equivalents		11.46B
Accounts Receivable		-995M
Inventory		2.66B
Goodwill		21.17B
Debt to Capitalization		0.78
Debt to Assets		0.43
Current Ratio		1.18
Quick Ratio		1.24

Metric
Rule of 40 (LTM)
Rule of 40 (NTM)
Stock Comp to Revenue		0.01
R&D to Revenue		0.21
SG&A to Revenue