Alzheimer disease: From AI prediction of pharmacotherapy to its drug formulation

Alzheimer disease (AD) is an age-associated neurodegenerative disorder. AD has been studied in the past three decades, yet no success medication is approved to date. The disease causing is a complex process and may involve multi-factorials which is a leading cause of death and a serious burden to families. AD is the most prevalent type of dementia and remains the fifth leading cause of death among Americans aged 65 and older. From literature review, two most disease-causing targets, namely, IDO1 and APOE4 are reported. In this study, we have chosen these two targets for new and or re-purpose molecules prediction by AI algorithm. The selected targets are believed to have potential in ameliorating the progression of AD. Target IDO1 is mainly involve in decreasing energy transfer to neuron. Inhibition of IDO1 may improve neuron energy transfer. As for APOE4, the processes mediated by APOE4, including cholesterol transport, synapse formation, modulation of neurite outgrowth, synaptic plasticity, destabilization of microtubules, and β-amyloid clearance, suggest potential therapeutic target. In this study, molecules that inhibit these two targets via AI prediction are conducted. Finally, an alternative method of NDA drug formulation using FDA drugs database and PAMPA dissolution is proposed for first in human (FIH) clinical study. The comparison between the use of FDA drugs’ ADME parameters and the new molecules’ in vitro ADME parameters for the design of FIH oral drug formulation is addressed.