| Metric | Value ($ M) | Q1 FY26 | Q2 FY25 |
|---|---|---|---|
| Revenue | 58.89 | 0.5% | 7.5% |
| Total Income | 58.89 | 0.5% | 7.5% |
| Expenditure | 100.44 | 6.5% | 6.7% |
| PBT | 7.35 | 112.3% | 117.1% |
| Net Profit | 5.98 | 110.0% | 113.8% |
| OPM | -70.55% | 12.73pp | 26.06pp |
| NPM | 10.15% | 88.99pp | |
| EPS | 0.08 | 109.9% | 113.6% |
Schrödinger Reports Q2 2026 Financial Results with 27% ACV Growth
06 Aug 2026 · 6 Aug, 1:47 am
Summary
Schrödinger announced strong second quarter results, with Annual Contract Value (ACV) growing 27% year-over-year to $29.6 million. Total revenue increased by 8% to $58.9 million, driven by a significant rise in drug discovery revenue to $23.0 million, boosted by a collaboration milestone. The company also reported a net income of $6.0 million, a substantial turnaround from a net loss in the previous year. Management highlighted the growing industry adoption of a predict-first approach and the launch of their new AI co-scientist, Bunsen, as key drivers for future growth.
Key Highlights
- 1
Schrödinger reported second quarter ACV of $29.6 million, representing a 27% increase year-over-year.
- 2
Total revenue for the second quarter was $58.9 million, an 8% increase compared to the prior year.
- 3
Software revenue decreased by 10% to $32.5 million, reflecting an accelerated transition to hosted software licensing.
- 4
Drug discovery revenue increased to $23.0 million, primarily due to a $10 million collaboration milestone.
- 5
Net income for the quarter was $6.0 million, a significant improvement from a net loss of $43.2 million in the prior year.
- 6
The company launched the early access version of Bunsen, its new agentic AI co-scientist for molecular discovery.
- 7
Schrödinger provided a financial outlook for the fiscal year ending December 31, 2026, expecting ACV to range from $218 million to $228 million.
Management Comments
Ramy Farid
We are very pleased with our second quarter results, delivering ACV of $29.6 million, which represents 27% growth. Our results reflect growing industry adoption of a predict-first approach to molecular discovery. As biopharma navigates a rapidly evolving AI landscape and mounting pressure to optimize and accelerate the discovery of new medicines, the need to generate ground-truth data has never been greater. By integrating our highly accurate, physics-based simulations with AI, and launching our agentic co-scientist Bunsen, we are enabling teams to execute complex workflows on a large scale and building the definitive computational infrastructure for the future of drug discovery.
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