ARTIFICIAL INTELLIGENCE POWERED DESIGN OF EXPERIMENTS: OPTIMIZING ABIRATERONE ACETATE LOADED GELATIN NANOPARTICLES FOR ENHANCED ORAL BIOAVAILABILITY OF ABIRATERONE ACETATE

ARTIFICIAL INTELLIGENCE POWERED DESIGN OF EXPERIMENTS: OPTIMIZING ABIRATERONE ACETATE LOADED GELATIN NANOPARTICLES FOR ENHANCED ORAL BIOAVAILABILITY OF ABIRATERONE ACETATE NALLAMUTHU M. https://orcid.org/0009-0002-5003-720X UMADEVI S. https://orcid.org/0000-0003-0242-2461 ANANDAN R. https://orcid.org/0000-0001-5461-1040

Objective: The current probing aims to investigate the Artificial Intelligence (AI) powered Design of Experiments (DoE) to optimize Abiraterone acetate loaded Gelatin Nanoparticles (AGNPs) with the desired Critical Quality Attributes (CQA) for increasing oral bioavailability of abiraterone acetate. Methods: AGNPs were formulated using the desolvation method, guided by a quality-by-design (QbD) approach, to identify CQA. The proposed DoE was a Central Composite Design (CCD) that was done to determine the influence of gelatin, tween 80, and genipin on particle size and Drug Entrapment Efficiency (DEE). Further optimization was performed with Artificial Neural Networks (ANN) to refine the predictive models. Results: The ANN model was developed using data from the CCD. K-fold cross-validation was implemented for training and validating the model. Both training and validation sets' R-squared values were closer to 1, confirming that the algorithms correctly characterized the predictive models. Characterization studies confirmed that optimized AGNPs had particle size (123.4±0.06 nm), poly dispersibility index (0.047±0.07), DEE (88.23±0.26 %), zeta potential (+35.78±0.24 mV), and controlled drug release (96.32±0.78 % over 12 h). Conclusion: The results show that nanoparticles developed according to the criteria set by CQA to enhance oral bioavailability, and an AI-integrated CCD approach optimally worked for AGNPs, which can deliver abiraterone acetate orally. The infusion of advanced technologies ANN undoubtedly holds excellent potential for exciting discoveries in nanomedicine and enables future innovations.
07 07 2025 483 496 https://creativecommons.org/licenses/by/4.0 10.22159/ijap.2025v17i4.54437 https://journals.innovareacademics.in/index.php/ijap/article/view/54437 https://journals.innovareacademics.in/index.php/ijap/article/download/54437/32298 https://journals.innovareacademics.in/index.php/ijap/article/download/54437/32298 https://journals.innovareacademics.in/index.php/ijap/article/download/54437/32356 10.1038/s41416-020-0859-x Butler EN, Kelly SP, Coupland VH, Rosenberg PS, Cook MB. Fatal prostate cancer incidence trends in the United States and England by race stage and treatment. Br J Cancer. 2020;123(3):487-94. doi: 10.1038/s41416-020-0859-x, PMID 32433602. 10.1056/NEJMoa1704174 Fizazi K, Tran N, Fein L, Matsubara N, Rodriguez Antolin A, Alekseev BY. Abiraterone plus prednisone in metastatic castration sensitive prostate cancer. N Engl J Med. 2017;377(4):352-60. doi: 10.1056/NEJMoa1704174, PMID 28578607. 10.1200/JCO.2008.20.0642 Attard G, Reid AH, A Hern RA, Parker C, Oommen NB, Folkerd E. Selective inhibition of CYP17 with abiraterone acetate is highly active in the treatment of castration resistant prostate cancer. J Clin Oncol. 2009;27(23):3742-8. doi: 10.1200/JCO.2008.20.0642, PMID 19470933. Goldberg T, Berrios Colon E. Abiraterone (zytiga) a novel agent for the management of castration resistant prostate cancer. PT. 2013;38(1):23-6. PMID 23599666. 10.1016/j.ijpharm.2020.119069 Schultz HB, Meola TR, Thomas N, Prestidge CA. Oral formulation strategies to improve the bioavailability and mitigate the food effect of abiraterone acetate. Int J Pharm. 2020 Mar 15;577:119069. doi: 10.1016/j.ijpharm.2020.119069, PMID 31981706. 10.22159/ijcpr.2023v15i6.3076 Imam SS. Nanoparticles: the future of drug delivery. Int J Curr Pharm Sci. 2023;15(6):8-15. doi: 10.22159/ijcpr.2023v15i6.3076. 10.3390/molecules25163731 Zielinska A, Carreiro F, Oliveira AM, Neves A, Pires B, Venkatesh DN. Polymeric nanoparticles: production characterization toxicology and ecotoxicology. Molecules. 2020;25(16):3731. doi: 10.3390/molecules25163731, PMID 32824172. 10.3389/fbioe.2023.1158749 Jiang X, Du Z, Zhang X, Zaman F, Song Z, Guan Y. Gelatin-based anticancer drug delivery nanosystems: a mini review. Front Bioeng Biotechnol. 2023 Mar 21;11:1158749. doi: 10.3389/fbioe.2023.1158749, PMID 37025360. 10.3390/polym3031377 Makadia HK, Siegel SJ. Poly lactic-co-glycolic acid (PLGA) as biodegradable controlled drug delivery carrier. Polymers (Basel). 2011;3(3):1377-97. doi: 10.3390/polym3031377, PMID 22577513. 10.1016/j.addr.2009.09.004 Kean T, Thanou M. Biodegradation, biodistribution and toxicity of chitosan. Adv Drug Deliv Rev. 2010 Jan 31;62(1):3-11. doi: 10.1016/j.addr.2009.09.004, PMID 19800377. 10.1016/j.jconrel.2023.07.018 Richfield O, Piotrowski Daspit AS, Shin K, Saltzman WM. Rational nanoparticle design: optimization using insights from experiments and mathematical models. J Control Release. 2023 Aug;360:772-83. doi: 10.1016/j.jconrel.2023.07.018, PMID 37442201. 10.1016/j.jconrel.2023.05.001 Rampado R, Peer D. Design of experiments in the optimization of nanoparticle-based drug delivery systems. J Control Release. 2023;358:398-419. doi: 10.1016/j.jconrel.2023.05.001, PMID 37164240. 10.22159/ajpcr.2024v17i11.52149 Podder S, Mukherjee S. Response surface methodology (RSM) as a tool in pharmaceutical formulation development. Asian J Pharm Clin Res. 2024;17(11):18-25. doi: 10.22159/ajpcr.2024v17i11.52149. 10.4103/2230-973X.82395 Singh B, Bhatowa R, Tripathi CB, Kapil R. Developing micro-/nanoparticulate drug delivery systems using design of experiments. Int J Pharm Investig. 2011;1(2):75-87. doi: 10.4103/2230-973X.82395, PMID 23071925. 10.1016/j.ejpb.2021.05.011 Tavares Luiz M, Santos Rosa Viegas J, Palma Abriata J, Viegas F, Testa Moura De Carvalho Vicentini F, Lopes Badra Bentley MV. Design of experiments (DoE) to develop and to optimize nanoparticles as drug delivery systems. Eur J Pharm Biopharm. 2021 Aug;165:127-48. doi: 10.1016/j.ejpb.2021.05.011, PMID 33992754. 10.3389/fmedt.2022.1067144 Das KP, JC. Nanoparticles and convergence of artificial intelligence for targeted drug delivery for cancer therapy: current progress and challenges. Front Med Technol. 2022;4:1067144. doi: 10.3389/fmedt.2022.1067144, PMID 36688144. 10.7759/cureus.47486 Vidhya KS, Sultana A, M NK, Rangareddy H. Artificial intelligence's impact on drug discovery and development from bench to bedside. Cureus. 2023;15(10):e47486. doi: 10.7759/cureus.47486, PMID 37881323. 10.3390/pharmaceutics15071916 Vora LK, Gholap AD, Jetha K, Thakur RR, Solanki HK, Chavda VP. Artificial intelligence in pharmaceutical technology and drug delivery design. Pharmaceutics. 2023;15(7):1916. doi: 10.3390/pharmaceutics15071916, PMID 37514102. 10.1016/j.drudis.2020.10.010 Paul D, Sanap G, Shenoy S, Kalyane D, Kalia K, Tekade RK. Artificial intelligence in drug discovery and development. Drug Discov Today. 2021;26(1):80-93. doi: 10.1016/j.drudis.2020.10.010, PMID 33099022. 10.3390/pharmaceutics14010183 Wang S, Di J, Wang D, Dai X, Hua Y, Gao X. State-of-the art review of artificial neural networks to predict characterize and optimize pharmaceutical formulation. Pharmaceutics. 2022;14(1):183. doi: 10.3390/pharmaceutics14010183, PMID 35057076. 10.1208/s12249-012-9836-x Aksu B, Paradkar A, De Matas M, Ozer O, Guneri T, York P. Quality by design approach: application of artificial intelligence techniques of tablets manufactured by direct compression. AAPS PharmSciTech. 2012;13(4):1138-46. doi: 10.1208/s12249-012-9836-x, PMID 22956056. 10.3897/pharmacia.71.e123549 Suriyaamporn P, Pamornpathomkul B, Wongprayoon P, Rojanarata T, Ngawhirunpat T, Opanasopit P. The artificial intelligence and design of experiment assisted in the development of progesterone loaded solid lipid nanoparticles for transdermal drug delivery. Pharmacia. 2024;71:1-12. doi: 10.3897/pharmacia.71.e123549. 10.1080/02664763.2021.1907840 Arboretti R, Ceccato R, Pegoraro L, Salmaso L, Housmekerides C, Spadoni L. Machine learning and design of experiments with an application to product innovation in the chemical industry. J Appl Stat. 2022;49(10):2674-99. doi: 10.1080/02664763.2021.1907840, PMID 35757041. 10.1208/s12248-014-9598-3 Yu LX, Amidon G, Khan MA, Hoag SW, Polli J, Raju GK. Understanding pharmaceutical quality by design. AAPS J. 2014;16(4):771-83. doi: 10.1208/s12248-014-9598-3, PMID 24854893. 10.1016/j.ajps.2016.07.006 Zhang L, Mao S. Application of quality by design in the current drug development. Asian J Pharm Sci. 2017 Jan;12(1):1-8. doi: 10.1016/j.ajps.2016.07.006, PMID 32104308. 10.1080/03639045.2017.1291672 N Politis S, Colombo P, Colombo G, M Rekkas D. Design of experiments (DoE) in pharmaceutical development. Drug Dev Ind Pharm. 2017;43(6):889-901. doi: 10.1080/03639045.2017.1291672, PMID 28166428. 10.3390/pharmaceutics13050702 Sipos B, Katona G, Csoka I. A systematic knowledge space-based proposal on quality by design-driven polymeric micelle development. Pharmaceutics. 2021;13(5):702. doi: 10.3390/pharmaceutics13050702, PMID 34065825. 10.3390/pharmaceutics15020514 Pielenhofer J, Meiser SL, Gogoll K, Ciciliani AM, Denny M, Klak M. Quality by design (QbD) approach for a nanoparticulate imiquimod formulation as an investigational medicinal product. Pharmaceutics. 2023;15(2):514. doi: 10.3390/pharmaceutics15020514, PMID 36839835. Krishnamoorthy K, Mahalingam M. Selection of a suitable method for the preparation of polymeric nanoparticles: multi-criteria decision making approach. Adv Pharm Bull. 2015;5(1):57-67. doi: 10.5681/apb.2015.008, PMID 25789220. 10.1080/02652048.2016.1228706 Geh KJ, Hubert M, Winter G. Optimisation of one-step desolvation and scale-up of gelatine nanoparticle production. J Microencapsul. 2016;33(7):595-604. doi: 10.1080/02652048.2016.1228706, PMID 27556342. 10.1080/17435889.2024.2359355 Silveira RF, Lima AL, Gross IP, Gelfuso GM, Gratieri T, Cunha Filho M. The role of artificial intelligence and data science in nanoparticles development: a review. Nanomedicine (Lond). 2024;19(14):1271-83. doi: 10.1080/17435889.2024.2359355, PMID 38905147. 10.1007/s11095-019-2620-9 Ismail R, Sovany T, Gacsi A, Ambrus R, Katona G, Imre N. Synthesis and statistical optimization of poly (lactic-Co-glycolic acid) nanoparticles encapsulating GLP1 analog designed for oral delivery. Pharm Res. 2019;36(7):99. doi: 10.1007/s11095-019-2620-9, PMID 31087188. 10.4103/1735-5362.199041 Salatin S, Barar J, Barzegar Jalali M, Adibkia K, Kiafar F, Jelvehgari M. Development of a nanoprecipitation method for the entrapment of a very water soluble drug into Eudragit RL nanoparticles. Res Pharm Sci. 2017;12(1):1-14. doi: 10.4103/1735-5362.199041, PMID 28255308. 10.1002/jps.20818 Bai G, Armenante PM, Plank RV, Gentzler M, Ford K, Harmon P. Hydrodynamic investigation of USP dissolution test apparatus II. J Pharm Sci. 2007;96(9):2327-49. doi: 10.1002/jps.20818, PMID 17573698. 10.3390/pharmaceutics14112324 Gonzalez Gonzalez O, Ramirez IO, Ramirez BI, O Connell P, Ballesteros MP, Torrado JJ. Drug stability: ICH versus accelerated predictive stability studies. Pharmaceutics. 2022;14(11):2324. doi: 10.3390/pharmaceutics14112324, PMID 36365143. 10.1016/j.actbio.2009.10.010 Liu TY, Lin YL. Novel pH-sensitive chitosan based hydrogel for encapsulating poorly water soluble drugs. Acta Biomater. 2010;6(4):1423-9. doi: 10.1016/j.actbio.2009.10.010, PMID 19819354. 10.3390/jpm11060571 Subhan MA, Yalamarty SS, Filipczak N, Parveen F, Torchilin VP. Recent advances in tumor targeting via EPR effect for cancer treatment. J Pers Med. 2021;11(6):571. doi: 10.3390/jpm11060571, PMID 34207137. 10.1016/j.carbpol.2015.07.072 Chang SH, Lin HT, Wu GJ, Tsai GJ. pH Effects on solubility zeta potential and correlation between Antibacterial Activity and Molecular Weight of chitosan. Carbohydr Polym. 2015;134:74-81. doi: 10.1016/j.carbpol.2015.07.072, PMID 26428102. 10.1016/j.yexmp.2008.12.004 Singh R, Lillard JW. Nanoparticle-based targeted drug delivery. Exp Mol Pathol. 2009;86(3):215-23. doi: 10.1016/j.yexmp.2008.12.004, PMID 19186176. 10.1517/17425247.2011.553216 Kita K, Dittrich C. Drug delivery vehicles with improved encapsulation efficiency: taking advantage of specific drug carrier interactions. Expert Opin Drug Deliv. 2011;8(3):329-42. doi: 10.1517/17425247.2011.553216, PMID 21323506. 10.1017/S0885715618000015 Wheatley AM, Kaduk JA, Gindhart AM, Blanton TN. Crystal structure of abiraterone acetate (Zytiga), C26H33NO2. Powder Diffr. 2018;33(1):72. doi: 10.1017/S0885715618000015. 10.1016/j.addr.2007.05.011 Blagden N, De Matas M, Gavan PT, York P. Crystal engineering of active pharmaceutical ingredients to improve solubility and dissolution rates. Adv Drug Deliv Rev. 2007;59(7):617-30. doi: 10.1016/j.addr.2007.05.011, PMID 17597252. 10.1007/s11095-017-2173-8 Shilpi D, Kushwah V, Agrawal AK, Jain S. Improved stability and enhanced oral bioavailability of atorvastatin loaded stearic acid modified gelatin nanoparticles. Pharm Res. 2017;34(7):1505-16. doi: 10.1007/s11095-017-2173-8, PMID 28466393. 10.3390/ijms23169491 Choi MJ, Woo MR, Choi HG, Jin SG. Effects of polymers on the drug solubility and dissolution enhancement of poorly water soluble rivaroxaban. Int J Mol Sci. 2022;23(16):9491. doi: 10.3390/ijms23169491, PMID 36012748. 10.1016/j.jconrel.2017.06.003 Al Kassas R, Bansal M, Shaw J. Nanosizing techniques for improving bioavailability of drugs. J Control Release. 2017 Aug 28;260:202-12. doi: 10.1016/j.jconrel.2017.06.003, PMID 28603030. 10.3797/scipharm.1210-02 Ali MS, Alam MS, Alam N, Anwer T, Safhi MM. Accelerated stability testing of a clobetasol propionate loaded nanoemulsion as per ICH guidelines. Sci Pharm. 2013;81(4):1089-100. doi: 10.3797/scipharm.1210-02, PMID 24482775.