This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.
Anil Kumar,
- M, Asst. Professor, School of Management Studies, GH Raisoni University, Amravati, Maharashtra, India
Abstract
Modern criminal investigations are inherently interdisciplinary, integrating medical research, forensic science, analytical chemistry, and artificial intelligence (AI) to transform hazy traces into reliable, legally recognised evidence. This study examines the ways in which different domains collaborate across the whole investigation process, ranging from judicial review, laboratory analysis, and computer processing to crime scene management and evidence retrieval. This research is based on a thorough review of scholarly literature and a comparative analysis of selected case studies from the US, UK, Japan, and India. According to the findings, the use of chemical and toxicological analysis, medico-legal examination, DNA profiling and database searches, and AI-enabled analytics—like pattern recognition, large-data triage, and image and video enhancement—all together greatly increases the speed, accuracy, and cross-case linkage of investigations. Case-based data shows that sophisticated DNA technology may successfully resolve cold cases, that attribution can be reinforced in chemical terrorism situations, and that biometric and digital systems can speed up suspect identification. Nevertheless, the findings also highlight new issues such as algorithmic opacity, weaknesses in data governance, and the danger of relying too much on probabilistic calculations. The study comes to the conclusion that AI shouldn’t replace scientific judgment but rather serve as an accelerator of evidence. Strict validation, openness, bias reduction, and standardised chain-of-custody norms are necessary for effective integration in order to guarantee judicial dependability and investigation effectiveness.
Keywords: analytical chemistry; medico-legal investigation; DNA profiling; toxicology; digital forensics; artificial intelligence; multidisciplinary integration; criminal investigation.
[This article belongs to Research and Reviews: A Journal of Toxicology ]
References
- Butler JM. Advanced topics in forensic DNA typing: interpretation. 2nd ed. Cambridge (MA): Academic Press; 2020.
- Casey E. Digital evidence and computer crime: forensic science, computers, and the internet. 4th ed. Cambridge (MA): Academic Press; 2021.
- Ferguson AG. The rise of big data policing: surveillance, race, and the future of law enforcement. New York (NY): New York University Press; 2017.
- Ribaux O, Baylon A, Lock E, Delémont O, Roux C, Zingg C, et al. Intelligence-driven crime scene processing. Forensic Sci Int. 2020;316:110546. doi:10.1016/j.forsciint. 2020.110546.
- Roth A. Machine testimony. Yale Law J. 2017;126(7):1972-2053.
- Siegel JA, editor. Forensic chemistry: fundamentals and applications. Chichester (UK): John Wiley & Sons; 2015.
- Walsh S, Chaitanya L, Clarisse L, Wirken L, Draus-Barini J, Kovatsi L, et al. Developmental validation of the HIrisPlex-S system for DNA-based eye, hair and skin colour prediction in forensic and anthropological usage. Forensic Sci Int Genet. 2021;53:102520. doi:10.1016/j.fsigen.2021.102520.
- Bell S. Forensic chemistry. 2nd ed. Upper Saddle River (NJ): Pearson Education; 2013.
- Houck MM, Siegel JA. Fundamentals of forensic science. 3rd ed. Amsterdam: Elsevier; 2015.
- Saferstein R. Criminalistics: an introduction to forensic science. 12th ed. Boston (MA): Pearson; 2018.
Research and Reviews: A Journal of Toxicology
| Volume | 16 | |
| Issue | 02 | |
| Received | 16/01/2026 | |
| Accepted | 03/07/2026 | |
| Published | 31/08/2026 | |
| Publication Time | 227 Days |