Υπολογιστική ανάπτυξη μοντέλων αξιολόγησης φαρμακοθεραπειών με χρήση αλγορίθμων μηχανικής εκμάθησης και ομικών δεδομένων
Keywords:
τεχνητή νοημοσύνη, μηχανική μάθηση, ανάπτυξη φαρμάκων, επανατοποθέτηση φαρμάκων, φαρμακευτική βιομηχανία
Abstract
Στην εποχή της ψηφιακής υγείας και της τεχνητής νοημοσύνης, επιτακτική καθίσταται η ανάγκη της φαρμακευτικής βιομηχανίας για καινοτόμες και μετασχηματιστικές τεχνολογίες ανάπτυξης φαρμάκων. Οι αλγόριθμοι τεχνητής νοημοσύνης και μηχανικής εκμάθησης, αν και αργά, έχουν αναμφισβήτητα αρχίσει να επιφέρουν επανάσταση στον τομέα ανάπτυξης φαρμάκων τα τελευταία πέντε έτη. Στη συγκεκριμένη ανασκόπηση, περιγράφουμε τις πιο συχνά χρησιμοποιούμενες προσεγγίσεις μηχανικής εκμάθησης στα εργαλεία ανάπτυξης φαρμάκων και τις βάσεις ομικών δεδομένων. Αναλύουμε τις νέες υπολογιστικές προσεγγίσεις στο πεδίο της ανακάλυψης φαρμάκων στο πλαίσιο της ανάπτυξης και επαναστόχευσης φαρμάκων, αλλά και τις συνέργειες μεταξύ των ομικών επιστημών, της τεχνητής νοημοσύνης και της μηχανικής εκμάθησης. Επιπρόσθετα, παραθέτουμε μια μελλοντική προοπτική σχετικά με τους τρόπους με τους οποίους οι προσεγγίσεις της μηχανικής εκμάθησης θα είναι εφικτό να εφαρμοστούν προκειμένου όχι απλώς να επισπεύσουν την ανακάλυψη φαρμάκων αλλά και να ενισχύσουν την Ιατρική Ακριβείας με κύριο γνώμονα το όφελος των ασθενών και της δημόσιας υγείας.
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