Author(s):
Joe Chou, Roger Lai, Jason Chou, Shelly Fu, Benjamin Chang
Email(s):
a0968288562@gmail.com
DOI:
10.52711/0975-4377.2024.00045 
Address:
Joe Chou1, Roger Lai2, Jason Chou1, Shelly Fu2, Benjamin Chang1
14th Floor, No. 366-1, Jilong Road Section 1, Taipei, Taiwan.
26F-11, No. 26, Tai-Yuen Street, ChuPei, Hsinchu, Taiwan.
*Corresponding Author
Published In:
Volume - 16,
Issue - 3,
Year - 2024
ABSTRACT:
Recent advancements in AI drug prediction have dramatically improved new drug candidate screening, facilitating more efficient identification of potential compounds. The success of a new drug application (NDA) relies on early-stage drug prediction and screening, preclinical studies,and PK/PD simulation prior to clinical study, underscoring the importance of accurate predictive models. Several essential databases, like Protein Data Bank (PDB), OpenTarget, PubChem, and ChemBL, SwissTarget etc., have made new drug searches easier with the help of fast AI computation, streamlining the drug discovery process. In drug dosage design, the oral formulation is still the most commonly needed due to its convenience in administration, emphasizing the significance of optimizing oral drug formulations for efficacy and patient compliance. Recent reports in oral new drug development have pointed out that PBPK modeling may lead to better prediction of ADME, offering a promising avenue for enhancing the understanding of drug behavior in the body. In addition, an alternative method using a FDA-approved PK database and PAMPA dissolution is also proposed to improve the development of NDA oral formulation, providing complementary approaches for formulation optimization. Therefore, a better prediction of an NCE from AI screening to clinical drug formulation could be conducted to enhance the success rate of oral NDA formulation development, fostering advancements in drug delivery and therapeutic efficacy.
Cite this article:
Joe Chou, Roger Lai, Jason Chou, Shelly Fu, Benjamin Chang. Oral NDA Research from AI Prediction to Clinical Drug Formulation. Research Journal of Pharmaceutical Dosage Forms and Technology.2024; 16(3):289-2. doi: 10.52711/0975-4377.2024.00045
Cite(Electronic):
Joe Chou, Roger Lai, Jason Chou, Shelly Fu, Benjamin Chang. Oral NDA Research from AI Prediction to Clinical Drug Formulation. Research Journal of Pharmaceutical Dosage Forms and Technology.2024; 16(3):289-2. doi: 10.52711/0975-4377.2024.00045 Available on: https://rjpdft.com/AbstractView.aspx?PID=2024-16-3-14
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