SDGR Stock: Insider Activity, Filings & Research

Schrödinger, Inc. (SDGR) — Drillr’s hub for SDGR insider activity, SEC filings, earnings signals and AI research. Over the trailing 3 months, SDGR insiders filed 0 open-market buys and 2 sales (SEC Form 4).

Sentiment

0/100

Buys (3m)

Sells (3m)

Net (3m)

-$541.0K

Insider trades by month Buys Sells

Mar

Apr

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Apr

Context3-month price +13.8%Institutions mixed (13F)

Date	Insider	Type	Shares	Price
Apr 17, 2026	Jain Rachitofficer: EVP & CFO	Sell	844	$12.75
Apr 17, 2026	Farid Ramydirector, officer: President & CEO	Option	74,527	$3.07
Apr 17, 2026	Farid Ramydirector, officer: President & CEO	Sell	43,000	$12.33
Apr 17, 2026	Farid Ramydirector, officer: President & CEO	Option	43,000	$3.07
Mar 6, 2026	Herman Jennyofficer: CAO	Sell	775	$12.85
Mar 6, 2026	Jain Rachitofficer: EVP & CFO	Sell	1,631	$12.90
Mar 6, 2026	Herman Jennyofficer: CAO	Sell	608	$12.84
Mar 6, 2026	Tran Yvonneofficer: EVP, CLO & CPO	Sell	1,094	$12.89
Mar 6, 2026	Abel Robert Lorneofficer: See Remarks	Sell	1,300	$12.81
Mar 6, 2026	Lorton Kenneth Patrickofficer: EVP, CTO & COO, Software	Sell	1,222	$12.90
Mar 6, 2026	Akinsanya Karenofficer: See Remarks	Sell	1,366	$12.90
Mar 6, 2026	Farid Ramydirector, officer: President & CEO	Sell	3,661	$12.91
Feb 12, 2026	Herman Jennyofficer: CAO	Sell	752	$13.79
Feb 12, 2026	Tran Yvonneofficer: EVP, CLO & CPO	Sell	776	$13.80
Feb 12, 2026	Lorton Kenneth Patrickofficer: EVP, CTO & COO, Software	Sell	925	$13.73

Source: SDGR SEC Form 4 filings, latest Apr 17, 2026. For informational purposes only — not investment advice.

Overview

Schrödinger, Inc. (NASDAQ:SDGR) is a computational platform company founded in 1990 and headquartered in New York, New York. The company went public in February 2020 and operates at the intersection of physics-based computational methods and drug discovery. Schrödinger has evolved from a software company serving the pharmaceutical industry into a dual-business model enterprise that both licenses its computational platform to external customers and develops its own proprietary drug candidates. The company serves biopharmaceutical companies, industrial firms, academic institutions, and government laboratories worldwide.

Business

Schrödinger operates in the computational drug discovery and materials science industry, providing physics-based software platforms that enable the discovery of novel molecules. The company's core technology uses advanced computational methods, including molecular dynamics simulations, quantum mechanics, and machine learning, to predict how molecules will behave and interact with biological targets before they are synthesized in the laboratory. The company operates through two primary business segments: 1. Software Segment (~87% of revenue): This division develops and licenses computational software platforms for drug discovery and materials science applications. The software helps pharmaceutical companies and researchers design better drug molecules by predicting their properties, toxicity, and effectiveness before expensive laboratory testing. The platform includes tools for molecular modeling, protein structure prediction, and drug-target interaction analysis. Customers can access the software through on-premise installations or hosted cloud-based solutions, with hosted revenue representing approximately 20% of software revenue and growing rapidly. 2. Drug Discovery Segment (~13% of revenue): This division focuses on developing proprietary drug candidates using the company's computational platform. Schrödinger currently has three clinical-stage oncology programs: SGR-1505 (a MALT1 inhibitor for B-cell lymphomas), SGR-2921 (a CDC7 inhibitor for blood cancers), and SGR-3515 (a Wee1/Myt1 co-inhibitor for solid tumors). The company also maintains a pipeline of preclinical programs across oncology, immunology, and neuroscience. The company's platform essentially acts as a computational laboratory that can simulate molecular interactions at the atomic level, helping researchers understand why certain drugs work or fail, and guiding the design of more effective therapeutics with fewer side effects.

Revenue model

Schrödinger generates revenue through multiple complementary business models. The Software segment operates on a licensing model, selling annual contracts to pharmaceutical companies, biotech firms, academic institutions, and materials science companies. Revenue comes from both on-premise software licenses and hosted cloud-based solutions, with customers typically paying annual contract values ranging from hundreds of thousands to millions of dollars. The company has successfully grown its customer base of high-value accounts, increasing customers with annual contract values over $5 million from 4 to 8 in 2024. The Drug Discovery segment generates revenue through collaboration agreements with pharmaceutical partners, milestone payments, and potential future royalties. Recent major partnerships include a collaboration with Novartis worth $150 million upfront with potential milestone payments up to $2.3 billion, plus royalties on commercial sales. The segment also benefits from distributions when co-founded or invested companies achieve successful exits, such as the $147 million received from Nimbus Therapeutics. Several factors influence the company's margins and growth potential. Positive factors include the increasing adoption of computational methods in drug discovery as pharmaceutical companies seek to improve R&D efficiency and reduce development costs and timelines. The growing emphasis on reducing animal testing in preclinical research also favors computational approaches. The company's high customer retention rate (100% for customers with annual contract values over $500,000) demonstrates strong customer stickiness. Challenging factors include the cyclical nature of biotech funding, which affects smaller customers' ability to purchase software licenses. Competition from other computational platforms and the emergence of AI-focused drug discovery companies could pressure pricing and market share. The drug discovery segment faces typical pharmaceutical development risks, including clinical trial failures and regulatory hurdles. Additionally, the company's significant R&D investments and cash burn create pressure to demonstrate clinical and commercial success.

Competitive moat

Schrödinger's competitive moat is moderately strong but faces emerging challenges. The company's primary moat stems from its deep expertise in physics-based computational methods and its comprehensive platform that combines quantum mechanics, molecular dynamics, and machine learning. This scientific depth, built over more than three decades, creates significant barriers for new entrants who would need years to develop comparable capabilities. The company benefits from high switching costs for customers who have integrated Schrödinger's software into their drug discovery workflows. Training scientists to use computational platforms requires substantial time investment, and the software often becomes embedded in critical research processes. The 100% retention rate for large customers demonstrates this stickiness. However, the moat faces potential erosion from several sources. The rise of AI-native drug discovery companies using large language models and deep learning approaches could disrupt traditional physics-based methods. Companies like DeepMind (AlphaFold) and numerous AI-focused biotech startups are developing alternative approaches that may prove more efficient or accessible. Additionally, large technology companies with substantial AI capabilities could enter the space with significant resources. The company's network effects are limited compared to true platform businesses, as customers primarily use the software independently rather than benefiting from other users' activities. While Schrödinger has built valuable partnerships with pharmaceutical companies, these relationships are not exclusive and could be replicated by competitors. The company's drug discovery segment provides additional differentiation but also increases execution risk and capital requirements.

Risks & safety

Schrödinger presents a moderate margin of safety with strong liquidity but ongoing profitability challenges. • Cash and Liquidity: Strong cash position of $326 million as of Q1 2025, providing substantial runway despite negative free cash flow of -$165 million in 2024. Current ratio of 3.45 indicates solid short-term liquidity. • Debt and Solvency: Low debt-to-equity ratio of 0.31, indicating conservative capital structure with minimal solvency risk in the near term. • Profitability and Cash Flow: Significant cash burn with negative EBITDA of -$209 million in 2024, though Q1 2025 showed positive operating cash flow of $144 million, suggesting potential improvement in cash management. • Valuation Metrics: Trading at negative P/E ratios due to losses, but Graham Net-Net ratio of 2.0 suggests the stock trades below net current asset value, providing some downside protection. • Other Considerations: Revenue growth of 13% in software segment provides some stability, but drug discovery segment volatility and high R&D expenses create ongoing cash flow uncertainty.

Recent development

Over the past few years, Schrödinger has executed several strategic pivots and expansions. The company has significantly expanded its drug discovery operations, advancing three proprietary programs into clinical trials: SGR-1505 (MALT1 inhibitor), SGR-2921 (CDC7 inhibitor), and SGR-3515 (Wee1/Myt1 co-inhibitor). Initial clinical data from these programs is expected throughout 2025, representing a critical inflection point for the company's therapeutic ambitions. The company has also strengthened its partnership strategy, most notably through a major collaboration with Novartis announced in 2024 that includes both expanded software licensing and drug discovery collaboration worth $150 million upfront with potential milestone payments exceeding $2 billion. This partnership validates Schrödinger's platform capabilities and provides significant financial resources. Technology development has focused on expanding beyond traditional small molecule drug discovery. The company launched a predictive toxicology initiative supported by a $10 million grant from the Bill & Melinda Gates Foundation, aiming to predict off-target protein binding and reduce drug development failures. New capabilities include enhanced biologics discovery technologies, crystal structure prediction software, and machine learning-based T cell receptor structure prediction. The company has also evolved its software delivery model, with hosted cloud-based solutions growing rapidly to represent 20% of software revenue. This shift toward software-as-a-service delivery provides more predictable revenue streams and easier customer onboarding. Additionally, Schrödinger has successfully scaled its high-value customer relationships, doubling the number of customers with annual contract values over $5 million.

SDGR company profile · for informational purposes only — not investment advice.

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