As medical professionals, staying up-to-date with the latest research and treatments is crucial. However, according to census research, 50% of what a well-established medical professional has learned needs to be updated, which can account for 25% of cases of negligence.[1]
To address this issue, ORA (Oncology AI Research Assistants) was created as a tool that continuously scours every single research paper and method being practised related to oncology in real-time. ORA's primary function is to extract insights and potentially overlooked treatments that can be used to deliver personalized and evidence-based support to cancer patients, particularly those with difficult-to-treat stomach cancer. By developing hand-in-hand with medical professionals, AI research assistants like ORA can evolve to meet the growing demand for efficient and effective solutions for complex medical cases.
In a recent case study, an AI research assistant was deployed to assist in treating a patient with stomach cancer [2]. The research assistant provided evidence-backed information that was concise, up-to-date, and realistic. It also provided step-by-step guides on approaching the unique situation presented by the patient’s stomach cancer.
The first step in the process was genetic analysis and precision medicine [1]. Stomach cancer is a complex disease with multiple subtypes, each of which has different genetic and molecular characteristics [3], so it is essential to understand which type of stomach cancer the patient has and whether it has any specific mutations or genetic markers that may be targeted through precision medicine techniques [4]. This could be done through genomic sequencing or other specialized technologies such as next-generation sequencing (NGS).
Oncologists now stand at the forefront of developing advanced therapies for personalized care. With the assistance of an AI research assistant, treatment recommendations can be developed by carefully analyzing up-to-date medical studies [5], potential success rates for particular cases, and existing guidelines for treating stomach cancer [6]. These comprehensive reviews enable doctors to prescribe the most advanced treatments available and tailor them to individual needs. [8].
Genetic Analysis and Precision Medicine: Stomach cancer is a complex disease with multiple subtypes, and each subtype has different genetic and molecular characteristics [1]. To understand the specific type of stomach cancer the patient has and whether it has any specific mutations or genetic markers that may be targeted through precision medicine techniques, a thorough genetic analysis is required. This could be done through genomic sequencing or using other specialized techniques such as CRISPR9 [1]. Once the genetic analysis is complete, personalized medicine and targeted therapies that may be more effective in treating the patient’s specific cancer can be explored [1]. Recent research in this field includes identifying potential therapeutic targets for stomach cancer based on genetic mutations [10].
Autophagy is a natural cellular process that removes damaged or unnecessary components from cells [3]. Recent research has shown that inducing autophagy in cancer cells can help destroy them by triggering programmed cell death, making it a potential treatment for stomach cancer [3]. Some studies have also explored the potential use of autophagy inhibitors as a therapeutic approach to treating cancer [10].
Cutting-edge research chemicals, peptides, and peptoids: Recent research has explored advanced research chemicals, peptides, and peptoids to help target and destroy cancer cells [10]. Some examples of research chemicals that have been investigated as potential anti-cancer agents include natural products such as curcumin and epigallocatechin-3-gallate (EGCG) [10]. Peptides and peptoids have also been explored as possible treatments for cancer due to their ability to selectively bind to cancer cells and induce cell death [10]. Further research in this field may provide novel approaches to treating stomach cancer.
Overall, advanced AI solutions have the potential to bridge the gap between the needs of patients with complex medical conditions and the lack of specialized care available for them. These tools can offer an effective and efficient solution to difficult-to-treat cases by providing personalised and evidence-based support. As these solutions evolve, they will be best served by advancing their algorithms and developing hand-in-hand with medical professionals providing up-to-date medical reports, peer-reviewed and ready for adoption.