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14 Pharmaceutical Technology ® Trends in Formulation 2022 eBook PharmTech.com PHOTON_PHOTO - STOCK.ADOBE.COM N ovel APIs are incredibly hard to identi- fy, and they occupy a special place in the annals of demanding pursuits for the betterment of mankind. But the hard work does not simply stop when a great new drug is unearthed. Formulating this new entity, which is now more frequently challenging to solubilize, stabilize, or store as we engage with more unusu- al or extreme structured molecules, is a complex and risky process in and of itself. Route of admin- istration must be evaluated and considered as an integral engineering task. This is difficult enough for tablets, capsules, or in- halation, but rises in degrees of freedom for innova- tive emerging therapies where in situ forming gels, polymer conjugate systems for controlled release or intravenous, intramuscular, or subcutaneous injec- tion is the desired delivery method. Obstacles to productivity Chris Moreton, Founder, of FinnBrit Consulting goes directly to the heart of the matter when he points to predictability of complex systems as being an obsta- cle to productivity. "There are several enabling tech- nologies for poorly water-soluble compounds: amor- phous solid dispersions, co-cr ystals, supercritical f luid processing to obtain nanoparticles, co-solvents, nanomilling, nanocrystallization, selfemulsif ying drug delivery systems (SEDDS), and self-micro-emul- sifying drug delivery systems (SMEDDS). We cannot always predict which one will be best for a particu- lar drug candidate with any certainty." He continues Machine Learning Provides a New Direction in Drug Formulation Chris Spivey, editorial director This article describes how to achieve better drug candidate path prediction through machine learning.