ArticleMethods in molecular biology (Clifton, N.J.)2025
AI-Assisted Cell Culture System.
Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Challenges and solutions for upstream processing of complex biologics.Antibody therapeutics · 2026Review
- AI-Driven Innovations for Quality Control and Standardization: Future Strategies in Adipose-Derived Stem Cell Manufacturing.International journal of molecular sciences · 2026Review
- Patient-derived organoids in gastric cancer: bridging the tumor microenvironment to functional precision oncology.Frontiers in bioengineering and biotechnology · 2026Review
- AI-driven strategies for advancing corneal cell therapy: a promising frontier.Frontiers in medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) proves to be a great tool that makes it possible for machines to learn from experience, regulate to new inputs, and execute human-like activities. AI is already the prime driver of emerging technologies and there are further possibilities in different fields. Certainly, the technology has not yet reached its full effectiveness in many fields but there is one area where AI, integrated with automation, can greatly improve laboratory research known as cell culture. Cell culture is an essential component of present-day biomedical research, allowing researchers to study cellular activities and underlying mechanisms of different diseases in a controlled laboratory setup and environment. Conventional cell culture procedures are hands-on procedures that are time engrossing, susceptible to error and variability, making it difficult to conduct large-scale investigations or screen large numbers of probable drug candidates. Application of AI and automated cell culture procedures can improve the reproducibility of the cell culture protocols that leads to less variability, better conclusions, and finally improving in-depth investigation and drug development. AI algorithms examine data from sensors and cameras to detect alterations in cell behavior, such as changes in appearance, morphology, or growth rate, and make adaptations to the culture conditions in real-time to optimize the growth and health of the cells. Robotic systems automate cell culture tasks, while AI algorithms monitor cell behavior and make adjustments to the culture conditions in real time. AI is considered a significant game changer in 3D cell culture as researchers can grow spheroids or organoids from different cell sources simultaneously, which will ensure consistency and reproducibility. Further, researchers and scientists can create customized workflows and protocols that follow the natural flow of the cell culture process without the need for modularization and human intervention through the use of AI. Though the AI application to cell culture system offers significant change to the scientists, the laboratories, and the companies, there are different aspects of AI applications that need to be considered through vast exploration.
Indexed as
Identifiers
40553332What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.