--- title: 'Software Daily Summary: What Happened on October 8, 2026' headline: Life-sciences tech spending plans reach a four-year high, Pistoia survey finds description: A review calls for AI systems that forecast pathogen evolution to be checked against experiments and evaluated across populations and time periods. url: https://thebench.bio/news/software/2026-10-08 topic: software date: '2026-10-08' covers: - '2026-10-08' date_published: '2026-10-08T12:03:54Z' date_modified: '2026-10-08T12:03:54Z' sources: 2 publisher: The Bench (thebench.bio) --- # Software Daily Summary: What Happened on October 8, 2026 **Life-sciences tech spending plans reach a four-year high, Pistoia survey finds** A review calls for AI systems that forecast pathogen evolution to be checked against experiments and evaluated across populations and time periods. ## Today in brief The Pistoia Alliance found that 76% of surveyed life-sciences respondents plan to increase technology spending over the next two years, up from 63% in 2025. [1] Chakraborty and Bhattacharya call for AI systems to forecast pathogen evolution and resistance, with forecasts tested in experiments and evaluated across populations and time periods. [2] ## Life-sciences technology spending The Pistoia Alliance’s annual Lab of the Future findings show that 76% of respondents plan to increase technology spending over the next two years, compared with 63% in 2025. [1] The Alliance’s data also identify a lack of leadership prioritization and support as the main obstacle to digital transformation in laboratories. [1] A peer-reviewed study backed by the Alliance analyzed 67 pharmaceutical AI use cases and found that business success was more closely associated with organizational maturity and leadership support than with the AI model or data source. [1] ## AI to anticipate pathogen change Chakraborty and Bhattacharya argue that clinical microbiology needs AI systems that forecast how pathogens evolve and develop resistance, helping guide prevention. [2] They recommend checking forecasts with confirmatory experiments, specifying actions tied to the forecasts, and evaluating the systems prospectively across different periods and populations. [2] They argue that oversight should address false alarms, model updates, and unequal performance as carefully as diagnostic errors. [2] ## The day in numbers - **76%**: Share of surveyed respondents planning to increase technology spending in the next two years, compared with 63% in 2025. [1] - **67**: Pharmaceutical AI use cases analyzed in the study, which found organizational maturity and leadership support more closely associated with business success than the model or data source. [1] ## Sources 1. [AI investment hits a four-year high as life sciences labs’ biggest barrier shifts from capacity to culture, Pistoia Alliance data finds ](), Pistoia Alliance, 2026-10-08 2. [Anticipatory intelligence in clinical microbiology](), Nature Reviews Bioengineering, 2026-10-08 --- The Bench wrote this from the reporting cited above, with a language model drafting and editing. [1]: [2]: