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Recent advancement in targeted therapy and role of emerging technologies to treat cancer

Shrikant Barot1, Henis Patel2, Anjali Yadav2

  • 1College of Pharmacy and Health Sciences, St. John's University, 8000 Utopia Parkway, Queens, NY, 11439, USA. Shrikant.barot15@stjohns.edu.

Medical Oncology (Northwood, London, England)
|October 7, 2023
PubMed

Insights

Personalized cancer treatments, including targeted therapies and immunotherapies, are advancing rapidly. Advanced technologies like artificial intelligence and next-generation sequencing are key to developing these innovative and effective cancer care strategies.

Area of Science:

  • Oncology
  • Biotechnology
  • Bioinformatics

Background:

  • Cancer is a complex disease driven by genetic mutations and environmental factors, presenting challenges in treatment due to drug resistance and variability.
  • Conventional chemotherapy often faces limitations in efficacy and tolerability.
  • Advancements in genetic testing and computational tools are paving the way for more precise cancer interventions.

Purpose of the Study:

  • To review the development and challenges of novel targeted cancer therapies.
  • To explore the clinical outcomes of advanced treatments such as monoclonal antibodies, CAR-T therapy, and cancer vaccines.
  • To examine the role of artificial intelligence and machine learning in identifying new cancer treatment targets.

Main Methods:

  • Review of recent clinical trial data and scientific literature.
  • Analysis of emerging technologies including next-generation sequencing, digital pathology, and artificial intelligence.
  • Discussion of various targeted therapy modalities like monoclonal antibodies (mAbs), bispecific antibodies (BsAbs), bispecific T cell engagers (BiTEs), dual variable domain (DVD) antibodies, CAR-T therapy, and cancer vaccines.

Main Results:

  • Targeted therapies and immunotherapies demonstrate superior clinical outcomes and improved drug tolerability compared to conventional chemotherapies.
  • Next-generation sequencing enables inexpensive genetic testing, uncovering mutations treatable with specialized drugs.
  • Artificial intelligence and machine learning are instrumental in discovering patient-specific biological targets for personalized cancer treatment.

Conclusions:

  • Combination of novel therapies with advanced technologies promises to revolutionize cancer treatment paradigms.
  • Personalized medicine approaches, driven by genetic insights and AI, offer significant potential for improving patient survival and quality of life.
  • Ongoing research and clinical trials are crucial for validating and expanding the application of these cutting-edge cancer therapies.
Keywords:
AmivantamabArtificial intelligence in drug discoveryAxicabtagene ciloleucelCAR-TSacituzumab GovitecanSipuleucel-TTalimogene laherparepvecTargeted therapymRNA-lipoplex nanoparticles

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