In recent years, physiological pharmaceutical model PBPK has been applied more and more no matter in the research and development of new drugs or generic research. FDA, EMA, CFDA and the big pharmaceutical00 companies are introducing modeling and simulation tools to accelerate drug development efficiency. Many scientific research staff feed back PBPK is a very complex model. We often heard at the international conference, but feel very difficult to get started. Here are some experience with the use of the PBPK model. I hope to help you.
Q: What is the significance of PBPK in the development of the pharmaceutical industry?
A: PBPK is important for the development of new drugs, which can be used in all stages of the development of new drugs. In the early new drug development phase: screening, due to the lack of data in the body, it is difficult to choose the compounds with characteristics. With the development of the continuous advance, the focus compound get more and more detailed DMPK characteristics. And PBPK model can be further optimized this time. By comparing the difference of the model, we can further understand the characteristics of the compound DMPK, which is clear in the further exploration which part of the ADME we should focus on. On the other hand, we can predict the next test results based on the optimized PBPK model, which is advantageous to the next step of the experiment design.
Q: How to be familiar with the PBPK model faster and better?
A: Read the relevant literature, build models and optimize models by yourselves. If you do not have programming experience, you’d better use a commercial software such as GastroPlus to build the models. At the same time, you can exchange ideas with your peers.
Q: Where is the deficiency of current PBPK model?
A: There are so many details not enough understood about the process of the drug in the body. So the PBPK model is still rough. We can not accurately predict. So we have to wait a long time before we can see the maturation of PBPK. We are still at the beginning stage. There is one saying: don’t believe it’s result of the forecast, you need to think about it more and more. If you do not verify, it is very dangerous to believe the results of the prediction.