Last weekend, I had the privilege of speaking about my work in pharmacogenomics at the Singapore Pharmacy Congress. It was a good time of getting to meet old friends and network with the new generation of pharmacists.

Just as how pharmacokinetic (PK) modeling is useful in drug development to find new doses, PK modeling can be useful too in helping to stratify patients and tailor appropriate drug doses to their needs. In the era of precision medicine, there is a huge focus on pharmacogenomics (PGx). However, as mentioned in a morning session on PGx, any good pharmacist would know that PGx alone cannot answer the full story of drug exposure. Factors such as age, weight and renal clearance can also significantly impact drug exposure. PK models can also incorporate mixed effects, allowing us to model the impact of all these factors together to make a more holistic decision about the appropriate dosing for a patient.

My fellow clinical pharmacists in turn educated me on the challenges of implementing PGx in the clinical setting, as well as the need to evaluate the cost-benefit of pre-emptive PGx testing. A medication with a wide therapeutic index that can be titrated slowly for a chronic condition might not benefit as much from PGx testing as a medication for an acute condition such as a serious infection, where the appropriate dose needs to be given right away. Many other challenges in evaluating cost of PGx testing and the need to prioritize only the important drug-gene alerts come in to play too. It was indeed enlightening to learn more about what was happening in the hospitals.