Recommendation of precision medicine application in Indonesia from multiple perspective: a review

Abstract

Recently, precision medicine has gained much attention. Precision medicine helps reduce trial-and-error prescribing and minimize adverse drug reactions while improving the drug's effectiveness. Precision medicine is a medical method that seeks to maximize healthcare quality by tailoring the healthcare process to each patient's unique characteristics. In the era of rapid technological growth and data explosion, precision medicine's development has become very promising. Development of techniques for obtaining medical data; significant reductions in the cost of bio sequencing; massive development of computing tools, storage systems, and wireless communication systems; as well as the development of data analysis techniques based on artificial intelligence have all become significant driving forces in the advancement of precision medicine. In this manuscript, we summarized previous studies on precision medicine development. In addition, we discussed the opportunities and potential challenges of precision medicine development, particularly in Indonesia. Despite its promising potential, many challenges remain to be overcome to develop precision medicine. Good regulations for patient data ownership and clinical data-sharing, followed by sufficient data infrastructure and human resource capabilities, are the most critical factors in ensuring success in precision medicine. Moreover, guaranteeing data safety, patient privacy, and genome fairness are other issues that must be addressed.

Studi Literatur Regulasi dan Etika Artificial Intelligence (AI) dalam Kebijakan Kedokteran Presisi (Precision Medicine)

“…Beberapa metode atau teknologi AI yang banyak digunakan dalam precision medicine seperti pada kasus pembacaan hasil gambar berupa radiologi seperti rontgen dada (chest x-ray), diagnsosis gambar berupa Computer Tomography (CT) and Magnetic Resonance Imaging (MRI). AI digunakan dan berperan penting untuk membantu analisis gambar untuk deteksi dini kelainan dan penyakit, serta membantu tenega kesehatan untuk interpretasi hasil dari x-ray, serta mengidentifikasi pola dan anomali (anomaly detection) pada paru-paru [19]. Selanjutnya dalam dukungan keputusan klinis (decision support system), AI digunakan untuk memberikan peringatan secara akurat Author : Faisal Asadi (real-time) kepada penyedia layanan kesehatan untuk potensi masalah, interaksi obat, atau penyimpangan dari protokol standar dari AI itu sendiri [15].…”