AUSTRALIAN JOURNAL OF BIOMEDICAL RESEARCH
Review Article
Aug 22, 2025 48 21

Advances in Drug Discovery: Navigating Challenges and Embracing Innovation

Kamila Khikhmetova 1 *
1 Department of Biomedical Sciences, School of Medicine Nazarbayaev University, Astana, Kazakhstan* Corresponding Author
Australian Journal of Biomedical Research, 1(1), 2025, aubm005
Publication date: Aug 22, 2025
Full Text (PDF)

ABSTRACT

It takes ten to fifteen years for a compound to progress from its identification to regulatory approval as a drug. Drug discovery is complex and resource-intensive process in which more than 90% of compounds never make it from bench to bedside and eventually get rejected during the development process. Experimental drugs failures often occur due to poor target selection, inadequate preclinical models, unforeseen toxicity, lack of efficacy in human trials, and the complexity of disease mechanisms, which make it difficult to predict drug responses accurately. Additionally, drug discovery is slowed down by a lack of collaboration between academia and industry, limiting the timely exchange of knowledge and expertise. Artificial intelligence (AI) is becoming an important tool in drug discovery, offering new possibilities to overcome existing challenges. It can help researchers identify better drug targets, make the screening process more efficient, and optimize drug design, which could speed up development and improve success rates. However, use of AI is associated with certain drawbacks such as potential exacerbation of healthcare gaps, protection of sensitive patient data and a need for informed consent. This review aims to discuss key challenges that hinder drug development process and explore future directions to enhance the efficiency of drug discovery.

KEYWORDS

Artificial intelligence Disease mechanism Drug discovery Drug failure Personalized medicine

CITATION (Vancouver)

Khikhmetova K. Advances in Drug Discovery: Navigating Challenges and Embracing Innovation. Australian Journal of Biomedical Research. 2025;1(1):aubm005.
APA
Khikhmetova, K. (2025). Advances in Drug Discovery: Navigating Challenges and Embracing Innovation. Australian Journal of Biomedical Research, 1(1), aubm005.
Harvard
Khikhmetova, K. (2025). Advances in Drug Discovery: Navigating Challenges and Embracing Innovation. Australian Journal of Biomedical Research, 1(1), aubm005.
AMA
Khikhmetova K. Advances in Drug Discovery: Navigating Challenges and Embracing Innovation. Australian Journal of Biomedical Research. 2025;1(1), aubm005.
Chicago
Khikhmetova, Kamila. "Advances in Drug Discovery: Navigating Challenges and Embracing Innovation". Australian Journal of Biomedical Research 2025 1 no. 1 (2025): aubm005.
MLA
Khikhmetova, Kamila "Advances in Drug Discovery: Navigating Challenges and Embracing Innovation". Australian Journal of Biomedical Research, vol. 1, no. 1, 2025, aubm005.

REFERENCES

  1. Sertkaya A, Beleche T, Jessup A, et al. Costs of Drug Development and Research and Development Intensity in the US, 2000-2018. JAMA Netw Open. 2024;7(5):e2415445. doi: 10.1001/jamanetworkopen.2024.15445.
  2. Kim E, Yang J, Park S, et al. Factors Affecting Success of New Drug Clinical Trials. Ther Innov Regul Sci. 2023;57(5):737–50. doi: 10.1007/s43441-023-00509-1.
  3. Yuan T, Werman JM, Sampson NS. The pursuit of mechanism of action: uncovering drug complexity in TB drug discovery. RSC Chem Biol. 2021;2(2):423–40. doi: 10.1039/D0CB00226G.
  4. Gil C, Martinez A. Is drug repurposing really the future of drug discovery or is new innovation truly the way forward? Expert Opin Drug Discov. 2021;16(8):829–31. doi: 10.1080/17460441.2021.1912733.
  5. Annett S. Pharmaceutical drug development: high drug prices and the hidden role of public funding. Biol Futur. 2021;72(2):129–38. doi: 10.1007/s42977-020-00025-5.
  6. Martins AC, Oshiro MY, Albericio F, et al. Trends and Perspectives of Biological Drug Approvals by the FDA: A Review from 2015 to 2021. Biomedicines. 2022;10(9):2325. doi: 10.3390/biomedicines10092325.
  7. Sun D, Gao W, Hu H, et al. Why 90% of clinical drug development fails and how to improve it? Acta Pharm Sin B. 2022;12(7):3049–62. doi: 10.1016/j.apsb.2022.02.002.
  8. Seyhan AA. Lost in translation: the valley of death across preclinical and clinical divide – identification of problems and overcoming obstacles. Transl Med Commun. 2019;4(1):18. doi: 10.1186/s41231-019-0050-7.
  9. Hwang TJ, Carpenter D, Lauffenburger JC, et al. Failure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results. JAMA Intern Med. 2016;176(12):1826. doi: 10.1001/jamainternmed.2016.6008.
  10. Fogel DB. Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review. Contemp Clin Trials Commun. 2018;11:156–64. doi: 10.1016/j.conctc.2018.08.001.
  11. Neumora Therapeutics Reports Data from KOASTAL-1 Study of Navacaprant in Major Depressive Disorder [Internet]. [cited 2025 Feb 20]. Available from: https://www.neumoratx.com/news
  12. Bazzari FH, Bazzari AH. BACE1 Inhibitors for Alzheimer’s Disease: The Past, Present and Any Future? Molecules. 2022;27(24):8823. doi: 10.3390/molecules27248823.
  13. Tariot PN, Riviere M, Salloway S, et al. Reversibility of cognitive worsening observed with BACE inhibitor umibecestat in the Alzheimer’s Prevention Initiative (API) Generation Studies. Alzheimers Dement. 2024;20(11):7745–61. doi: 10.1002/alz.14237.
  14. Maher TM, Ford P, Brown KK, et al. Ziritaxestat, a Novel Autotaxin Inhibitor, and Lung Function in Idiopathic Pulmonary Fibrosis: The ISABELA 1 and 2 Randomized Clinical Trials. JAMA. 2023;329(18):1567. doi: 10.1001/jama.2023.5355.
  15. Amin NB, Frederich R, Tsamandouras N, et al. Evaluation of an oral small‐molecule glucagon‐like peptide‐1 receptor agonist, lotiglipron, for type 2 diabetes and obesity: A dose‐ranging, phase 2, randomized, placebo‐controlled study. Diabetes Obes Metab. 2025;27(1):215–27. doi: 10.1111/dom.16005.
  16. Biogen and Ionis announce topline Phase 1/2 study results [Internet]. [cited 2025 Feb 20]. Available from: https://investors.biogen.com/news-releases
  17. Opthea announces COAST Phase 3 trial topline results [Internet]. [cited 2025 Feb 20]. Available from: https://www.opthea.com/investor-centre/asx-announcements/
  18. Schriml LM, Lichenstein R, Bisordi K, et al. Modeling the enigma of complex disease etiology. J Transl Med. 2023;21(1):148. doi: 10.1186/s12967-023-03987-x.
  19. Bano I, Butt UD, Mohsan SAH. New challenges in drug discovery. In: Novel Platforms for Drug Delivery Applications. Elsevier; 2023. p. 619–43. doi: 10.1016/B978-0-323-91376-8.00021-5.
  20. Andrews SJ, Renton AE, Fulton-Howard B, et al. The complex genetic architecture of Alzheimer’s disease: novel insights and future directions. EBioMedicine. 2023;90:104511. doi: 10.1016/j.ebiom.2023.104511.
  21. Loewa A, Feng JJ, Hedtrich S. Human disease models in drug development. Nat Rev Bioeng. 2023;1(8):545–59. doi: 10.1038/s44222-023-00063-3.
  22. De Meyer A, Meuleman P. Preclinical animal models to evaluate therapeutic antiviral antibodies. Antiviral Res. 2024;225:105843. doi: 10.1016/j.antiviral.2024.105843.
  23. Moffat JG, Vincent F, Lee JA, et al. Opportunities and challenges in phenotypic drug discovery: an industry perspective. Nat Rev Drug Discov. 2017;16(8):531–43. doi: 10.1038/nrd.2017.111.
  24. Davis RL. Mechanism of Action and Target Identification: A Matter of Timing in Drug Discovery. iScience. 2020;23(9):101487. doi: 10.1016/j.isci.2020.101487.
  25. Emmerich CH, Gamboa LM, Hofmann MCJ, et al. Improving target assessment in biomedical research: the GOT-IT recommendations. Nat Rev Drug Discov. 2021;20(1):64–81. doi: 10.1038/s41573-020-0087-3.
  26. Tanoli Z, Schulman A, Aittokallio T. Validation guidelines for drug-target prediction methods. Expert Opin Drug Discov. 2025;20(1):31–45. doi: 10.1080/17460441.2024.2430955.
  27. Moustaqil M, Gambin Y, Sierecki E. Biophysical Techniques for Target Validation and Drug Discovery in Transcription-Targeted Therapy. Int J Mol Sci. 2020;21(7):2301. doi: 10.3390/ijms21072301.
  28. Kaelin WG. Common pitfalls in preclinical cancer target validation. Nat Rev Cancer. 2017;17(7):441–50. doi: 10.1038/nrc.2017.32.
  29. Qannita RA, Alalami AI, Harb AA, et al. Targeting Hypoxia-Inducible Factor-1 (HIF-1) in Cancer: Emerging Therapeutic Strategies and Pathway Regulation. Pharmaceuticals. 2024;17(2):195. doi: 10.3390/ph17020195.
  30. Weaver RJ, Valentin J-P. Today’s Challenges to De-Risk and Predict Drug Safety in Human “Mind-the-Gap.” Toxicol Sci. 2019;167(2):307–21. doi: 10.1093/toxsci/kfy270.
  31. Liu L, Wang C, Li S, et al. ERO1L Is a Novel and Potential Biomarker in Lung Adenocarcinoma and Shapes the Immune-Suppressive Tumor Microenvironment. Front Immunol. 2021;12:677169. doi: 10.3389/fimmu.2021.677169.
  32. Seol S-Y, Kim C, Lim JY, et al. Overexpression of Endoplasmic Reticulum Oxidoreductin 1-α (ERO1L) Is Associated with Poor Prognosis of Gastric Cancer. Cancer Res Treat. 2016;48(4):1196–209. doi: 10.4143/crt.2015.189.
  33. Chen P, Chen Y, Sharma A, et al. Inhibition of ERO1L induces autophagy and apoptosis via endoplasmic reticulum stress in colorectal cancer. Cell Signal. 2025;127:111560. doi: 10.1016/j.cellsig.2024.111560.
  34. Zhang J, Yang J, Lin C, et al. Endoplasmic Reticulum stress-dependent expression of ERO1L promotes aerobic glycolysis in Pancreatic Cancer. Theranostics. 2020;10(18):8400–14. doi: 10.7150/thno.45124.
  35. Blais JD, Chin K-T, Zito E, et al. A Small Molecule Inhibitor of Endoplasmic Reticulum Oxidation 1 (ERO1) with Selectively Reversible Thiol Reactivity. J Biol Chem. 2010;285(27):20993–1003. doi: 10.1074/jbc.M110.126599.
  36. Zhang Y, Li T, Zhang L, et al. Targeting the functional interplay between endoplasmic reticulum oxidoreductin-1α and protein disulfide isomerase suppresses the progression of cervical cancer. EBioMedicine. 2019;41:408–19. doi: 10.1016/j.ebiom.2019.02.041.
  37. Becher I, Werner T, Doce C, et al. Thermal profiling reveals phenylalanine hydroxylase as an off-target of panobinostat. Nat Chem Biol. 2016;12(11):908–10. doi: 10.1038/nchembio.2185.
  38. Pognan F, Beilmann M, Boonen HCM, et al. The evolving role of investigative toxicology in the pharmaceutical industry. Nat Rev Drug Discov. 2023;22(4):317–35. doi: 10.1038/s41573-022-00633-x.
  39. Su J, Yang L, Sun Z, et al. Personalized Drug Therapy: Innovative Concept Guided With Proteoformics. Mol Cell Proteomics. 2024;23(5):100737. doi: 10.1016/j.mcpro.2024.100737.
  40. Pandey A, Gupta SP. Personalized Medicine: A Comprehensive Review. Orient J Chem. 2024;40(4):933–44. doi: 10.13005/ojc/400403.
  41. Forgrave LM, Wang M, Yang D, et al. Proteoforms and their expanding role in laboratory medicine. Pract Lab Med. 2022;28:e00260. doi: 10.1016/j.plabm.2021.e00260.
  42. Vallée A. Envisioning the Future of Personalized Medicine: Role and Realities of Digital Twins. J Med Internet Res. 2024;26:e50204. doi: 10.2196/50204.
  43. Katsoulakis E, Wang Q, Wu H, et al. Digital twins for health: a scoping review. NPJ Digit Med. 2024;7(1):77. doi: 10.1038/s41746-024-01073-0.
  44. Li X, Loscalzo J, Mahmud AKMF, et al. Digital twins as global learning health and disease models for preventive and personalized medicine. Genome Med. 2025;17(1):11. doi: 10.1186/s13073-025-01435-7.
  45. Cellina M, Cè M, Alì M, et al. Digital Twins: The New Frontier for Personalized Medicine? Appl Sci. 2023;13(13):7940. doi: 10.3390/app13137940.
  46. S D, R K. A Review of the Regulatory Challenges of Personalized Medicine. Cureus [Internet]. 2024;16(5). doi: 10.7759/cureus.67891.
  47. Saqib U, Demaree IS, Obukhov AG, et al. The fate of drug discovery in academia; dumping in the publication landfill? Oncotarget. 2024;15:31–4. doi: 10.18632/oncotarget.28552.
  48. Shapiro MD, Tavori H, Fazio S. PCSK9: From Basic Science Discoveries to Clinical Trials. Circ Res. 2018;122(10):1420–38. doi: 10.1161/CIRCRESAHA.118.311227.
  49. Cheng F, Ma Y, Uzzi B, et al. Importance of scientific collaboration in contemporary drug discovery and development: a detailed network analysis. BMC Biol. 2020;18(1):138. doi: 10.1186/s12915-020-00868-3.
  50. Reddy SSK, Chao S. Academic Collaborations with Industry: Lessons for the Future. J Investig Med. 2020;68(8):1305–8. doi: 10.1136/jim-2020-001636.
  51. Tanaka ML, Lopez O. Outlook on Industry-Academia-Government Collaborations Impacting Medical Device Innovation. J Eng Sci Med Diagn Ther. 2024;7(2):025001. doi: 10.1115/1.4063464.
  52. Everts M, Drew M. Successfully navigating the valley of death: the importance of accelerators to support academic drug discovery and development. Expert Opin Drug Discov. 2024;19(3):253–8. doi: 10.1080/17460441.2023.2284824.
  53. Möhrle JJ. How long does it take to develop a new drug? Lancet Reg Health Eur. 2024;43:100998. doi: 10.1016/j.lanepe.2024.100998.
  54. O’Dwyer M, Filieri R, O’Malley L. Establishing successful university–industry collaborations: barriers and enablers deconstructed. J Technol Transf. 2023;48(3):900–31. doi: 10.1007/s10961-022-09932-2.
  55. Cama J, Leszczynski R, Tang PK, et al. To Push or To Pull? In a Post-COVID World, Supporting and Incentivizing Antimicrobial Drug Development Must Become a Governmental Priority. ACS Infect Dis. 2021;7(8):2029–42. doi: 10.1021/acsinfecdis.0c00681.
  56. Sullivan JA, Gold ER. Exploring regulatory flexibility to create novel incentives to optimize drug discovery. Front Med. 2024;11:1379966. doi: 10.3389/fmed.2024.1379966.
  57. Kiriiri GK, Njogu PM, Mwangi AN. Exploring different approaches to improve the success of drug discovery and development projects: a review. Futur J Pharm Sci. 2020;6(1):27. doi: 10.1186/s43094-020-00047-9.
  58. Pantanowitz L, Bui MM, Chauhan C, et al. Rules of engagement: Promoting academic-industry partnership in the era of digital pathology and artificial intelligence. Acad Pathol. 2022;9(1):100026. doi: 10.1016/j.acpath.2022.100026.
  59. Kint S, Dolfsma W, Robinson D. Strategic partnerships for AI-driven drug discovery: The role of relational dynamics. Drug Discov Today. 2024;29(4):104242. doi: 10.1016/j.drudis.2024.104242.
  60. Hoffmann J-M, Bauer A, Grossmann R. Academic vs. industry-sponsored trials: A global survey on differences, similarities, and future improvements. J Glob Health. 2024;14:04204. doi: 10.7189/jogh.14.04204.
  61. Roope LSJ. The economic challenges of new drug development. J Control Release. 2022;345:275–7. doi: 10.1016/j.jconrel.2022.03.023.
  62. Burton A, Castaño A, Bruno M, et al. Drug Discovery and Development in Rare Diseases: Taking a Closer Look at the Tafamidis Story. Drug Des Devel Ther. 2021;15:1225–43. doi: 10.2147/DDDT.S289772.
  63. Blanco-González A, Cabezón A, Seco-González A, et al. The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies. Pharmaceuticals. 2023;16(6):891. doi: 10.3390/ph16060891.
  64. Dara S, Dhamercherla S, Jadav SS, et al. Machine Learning in Drug Discovery: A Review. Artif Intell Rev. 2022;55(3):1947–99. doi: 10.1007/s10462-021-10058-4.
  65. Xu Y, Liu X, Cao X, et al. Artificial intelligence: A powerful paradigm for scientific research. Innovation. 2021;2(4):100179. doi: 10.1016/j.xinn.2021.100179.
  66. Farghali H, Kutinová Canová N, Arora M. The potential applications of artificial intelligence in drug discovery and development. Physiol Res. 2021;70(Suppl4):S715–22. doi: 10.33549/physiolres.934765.
  67. Ren F, Aliper A, Chen J, et al. A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models. Nat Biotechnol. 2025;43(1):63–75. doi: 10.1038/s41587-024-02143-0.
  68. Hasselgren C, Oprea TI. Artificial Intelligence for Drug Discovery: Are We There Yet? Annu Rev Pharmacol Toxicol. 2024;64(1):527–50. doi: 10.1146/annurev-pharmtox-040323-040828.
  69. Xie W, Zhang J, Xie Q, et al. Accelerating discovery of bioactive ligands with pharmacophore-informed generative models. Nat Commun. 2025;16(1):2391. doi: 10.1038/s41467-025-56349-0.
  70. Vidhya KS, Sultana A, M NK, et al. Artificial Intelligence’s Impact on Drug Discovery and Development From Bench to Bedside. Cureus [Internet]. 2023;15(9). doi: 10.7759/cureus.47486.
  71. Han R, Yoon H, Kim G, et al. Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery. Pharmaceuticals. 2023;16(9):1259. doi: 10.3390/ph16091259.
  72. Chau HC, Liu JYH, Rudd JA. An application of deep learning model InceptionTime to predict nausea, vomiting, diarrhoea, and constipation using the gastro-intestinal pacemaker activity drug database (GIPADD). Sci Rep. 2025;15(1):13105. doi: 10.1038/s41598-025-95961-4.
  73. Santa Maria JP, Wang Y, Camargo LM. Perspective on the challenges and opportunities of accelerating drug discovery with artificial intelligence. Front Bioinform. 2023;3:1121591. doi: 10.3389/fbinf.2023.1121591.
  74. Nishan MNH. AI-powered drug discovery for neglected diseases: accelerating public health solutions in the developing world. J Glob Health. 2025;15:03002. doi: 10.7189/jogh.15.03002.
  75. Boudi AL, Boudi M, Chan C, et al. Ethical Challenges of Artificial Intelligence in Medicine. Cureus [Internet]. 2024;16(7). doi: 10.7759/cureus.74495.
  76. Qureshi R, Irfan M, Gondal TM, et al. AI in drug discovery and its clinical relevance. Heliyon. 2023;9(7):e17575. doi: 10.1016/j.heliyon.2023.e17575.
  77. Marques A, Costa P, Velho S, et al. Analytical Techniques for Characterizing Tumor-Targeted Antibody-Functionalized Nanoparticles. Life. 2024;14(4):489. doi: 10.3390/life14040489.

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