Officially, Prof. Malcolm Rowland has retired. This scientific pioneer has been helping lay the foundation of a mechanistic understanding of pharmacokinetics since the 1960s. So you might think that he’d be ready for quieter pursuits. But this professor emeritus at the University of Manchester has no plans to stop actively teaching and guiding the pharmaceutical industry’s use of modeling and simulation. Here, we pick Prof. Rowland’s brain about the impact of pharmacometrics on drug development, the direction he sees the field going, and the secrets to his success as a scientist and teacher.
My trends in pharmacometrics and systems pharmacology Q&A with Prof. Rowland
Q. Can you discuss what attracted you to a career in science? What do you see as your current role?
A. I’ve always been fascinated with how the body handles drugs and chemicals in general. If one understood both the quantitative and qualitative processes controlling these events in vivo, and the factors that determine the magnitude of the processes, it should be possible to predict the pharmacokinetic behavior of drugs from first principles using physical, chemical, in vitro data and relevant physiological and biochemical data. That’s been a driving force for me over the years.
I started doing research in this field 50 years ago. My early publications date back to the ’60s. I’ve been involved with the field of physiologically based pharmacokinetics (PBPK) for many of these years. In my day, drug development was mainly empirical and descriptive. Now it’s more mechanistic and more predictive. I don’t have a laboratory or graduate students anymore. But, I interact with a lot of people in academia, industry and regulatory agencies discussing relevant issues, offering advice, and encouraging additional research to be done. As you know I’m on the scientific advisory boards of Simcyp and Certara. I also consult for the industry and teach courses. So, I’m not going to stop. I think they’ll have to carry me out!
Q. In an interview with the American Association of Pharmaceutical Sciences (AAPS), you mentioned your foster parents among your early influences. If you were to talk to a child in foster care today, what advice would you give to them?
A. That’s an interesting question. I would ask them to appreciate that education is the key to their future. That if they can get a good education, then they are well on their way. To do that, they need to gravitate to supportive people. I was very fortunate in that way. One of my foster parents was a teacher, so it was natural for them to support me in my education.
My experience has been that one important component of getting a good education is study. I didn’t know how much that would benefit me at the time, but I really enjoyed it. While personal studying is free in financial terms, it costs time and commitment. And when you’re young you don’t often realize that the time invested is worthwhile. So I would ask them to try to shy away from the bright lights. The instant gratification. The shallower things in life. Also respect others. That would be my advice to them.
Q. Can you talk about the adoption of PBPK models by the pharmaceutical industry and regulatory agencies and how that’s changing our approach to drug development?
A. Yes, the adoption of PBPK is very nice to see although it’s been slow in coming. I published my first PBPK paper in Clinical Pharmacology & Therapeutics in 1974. That was over 40 years ago! But, the actual research, of course, started before then. So, it isn’t as if the essence of the subject wasn’t thought about. We didn’t have the tools at that stage—the molecular tools, the in vitro tools, the computational tools—and the mechanistic knowledge that were necessary to move the subject forward.
What has also been necessary for PBPK to take off is the development of user-friendly software platforms. The Simcyp Simulator is an excellent example of that type of software. The receptivity by regulatory agencies has also greatly facilitated the uptake of PBPK by industry, which has now seen exponential growth in its application during the past decade.
There’s an analogy that I use to illustrate the importance of regulatory receptivity. Pharmacometrics uses nonlinear mixed effects modeling to characterize population variability and the factors, covariates, responsible for the variability. When this methodology was developed within academia in the ’80s and early ’90s, the industry did not take it seriously. But then the regulators said this approach was very important. They stated that sponsors needed to provide data about why people varied in their responses to drugs, what was responsible for that variability, and how that variability influences dosing regimens. Then, the industry responded. Now, leveraging this tool is second nature to pharma.
The same thing is happening now in the industrial application of PBPK. The partnerships between industry and Certara through the Simcyp Consortium are also facilitating the uptake of PBPK. This powerful resource-sparing approach is changing the course of drug development.
PBPK is mechanistic, rather than empirical. This approach lays down a scientific framework for acquiring the type and quality of physical, chemical, and in vitro data needed to improve clinical development. Without the right data, you can’t predict the pharmacokinetics in humans. Therefore, you can’t work out what your exposures are most likely to be in first-in-human studies.
To be successful, a drug developer must be able to answer multiple questions related to pharmacokinetics. How should I design clinical studies? When and how long do I need to collect PK samples? What is the relationship between the dose and exposure? All these questions were primarily driven by empiricism before the advent of PBPK. Some areas of drug development are still empirically-based. But without the frame of PBPK, you wouldn’t have been able to systematize thinking about the components needed to make sound predictions. I think you’ve seen that happen in the change that’s going on within the industry.
PBPK describes how drugs might behave in people on average. This approach can also look at the causes of variability in drug responses—genetics, other drugs, disease, food, smoking, etc. PBPK provides insight into what we would expect in these different situations, both individually and together. This tool has been very useful in clinical development. Also, PBPK allows prediction in special populations—pediatrics, pregnant women, or patients with severe organ impairment—who are unlikely to be studied at Phase 2 or Phase 3 clinical trials. So while we can’t always do clinical studies in these individuals, we do need guidance in drug labels as to what might be expected. Some of the more recent labels indicate that the sponsor used PBPK to make predictions related to particular drug- drug interactions.
Formulation development is another major application for PBPK, especially physiologically-based, mechanistic in vivo in vitro correlations (IVIVC). Understanding the interaction between the pharmaceutical formulation and its performance in vivo is critical. The industry is increasingly turning to PBPK to understand their drug’s dosage forms better and to reduce the number of clinical studies needed to get this information. The wise use of PBPK is transforming the way industry and regulators think about drugs and their use.
Q. We’ve talked about the use of modeling and simulation for clinical research. Among the many boards you served on was the National Center for Replacement, Refinement, and Reduction of Animals in Research. Can you comment on how modeling and simulation is impacting pre-clinical research?
A. Yes, Replacement, Refinement, and Reduction—commonly known as the Three Rs. I think that for too many years researchers have treated animals as objects rather than sentient creatures that feel pain and experience distress. We realize now that this attitude is not the way to go.
And I think people increasingly realize that while animal studies provide basic information about physiology, pathology, genetics, and more, they don’t completely map to human beings. Many important elements are unique to humans—distinct metabolism, transporter levels, disease pathophysiology, and environmental factors.
Animal research is still necessary for gaining a basic understanding of biological processes that would be very difficult to attain in humans. But animal studies are limited. We should look for alternative methodologies that not only substitute for experiments we might do in animals, but also are more relevant to human health.
For example, we can perform experiments using human tissues, enzyme systems, or transporters. These human in vitro systems will yield much more relevant information than what we’d get from animals. So we’ve seen an increasing prominence and acceptance of this view. Methodologies that minimize the need for animal studies— both human in vitro systems and in silico approaches— are also less costly. In many areas of drug development, including pharmacokinetics, animals are being used less to provide the information we need. Also, why expose animals to stress and pain in safety assessments with compounds whose pharmacokinetics in humans do not meet the developer’s requirements, when this could have been predicted using such a tool as PBPK?
Q. In 2012, you wrote a scientific article entitled, “The Impact of Pharmaceutical Sciences on Healthcare: A Reflection over the Past 50 Years.” Looking forward to the next 40 years, what would you predict will be the impact of this approach on healthcare?
A. This is an interesting question. Reviewing and reflecting upon the past 50 years with experienced colleagues was relatively easy. You’ve got to read a lot of publications and identify the critical ones. And, you only know which publications described critical and disruptive approaches by looking back. You can’t always see it at the time.
So, predicting even ten years from now what the situation will be is going to be highly problematic. Predicting the state of affairs 40 years from now requires someone braver (more foolhardy) than me!
However, I think we can say a number of things. We can say that mechanistically-based, quantitative, predictive approaches are likely to impact drug development right down to the individual patient level. These approaches will improve the individualization of medicines and therapeutics. And leveraging these tools through web-based and mobile phone technologies will become commonplace. In addition, patients will know a lot more about their genetics, health and disease, and hereditary risk factors.
The scientific community will also need to support the companion development of mechanistically-based pharmacodynamics—the body’s response to exposure to drugs. And this endeavor will need to move along the same broad lines that we’ve seen in the last 40 years for physiologically-based pharmacokinetics. We’re beginning to see this work develop for quantitative systems pharmacology and systems pharmacology and therapeutics. But, the field needs to advance much further. We need to understand how the body operates as a networked structure and the underlying pathophysiology of individual processes in the body.
In my opinion, developing mechanistically-based pharmacodynamics tools will improve the ability to predict drug efficacy. Most drugs that get into Phase 1 and go onto Phase 2 fail because of the lack of efficacy. Understanding mechanistically both PK and PD will help us develop safer, more effective drugs. We will be able to predict much earlier which drugs are likely to produce problems and stop their development. We won’t have to wait for reports of adverse events after these drugs are given to patients in large groups or out in the wider world. The measures of success for this effort will be threefold: a decrease in the likelihood of major adverse events, better understanding of the individual differences between patients, and greater individualizing of treatments.
In the next 40 years, the use of modeling and simulation (M&S, biosimulation) will become much more extensive. Modeling and simulation, already an integral part of PBPK, will permeate the whole drug selection, development and use programs. We’ll see the industry, increasingly, and society as a whole, benefiting from using M&S.
The population at large won’t see biosimulation in the way that industry or regulators see it. Just like they don’t see the use of computer models in weather forecasting. They don’t appreciate the mechanistic understanding and the massive computational power that is used in weather forecasting. They just see the weather forecast, and they are increasingly confident about whether they want to go out for a trip tomorrow morning or afternoon, or even three or more days later. The same is going to happen with drug development, which will become increasingly predictive and individualized. By knowing to whom and how much, how often, and for how long we need to give drugs to patients, healthcare will become more precise.
I also foresee a focus on developing drugs and other approaches that help the body to heal itself. One example of this can be seen in immunotherapy for oncology.
Q. Is there anything else that you’d like the readers of the Certara blog to know about you and your career?
A. Pharmacokinetics was virtually not discussed when I was young, even when I was going through my pharmacy education. We never had a course in pharmacokinetics.
Over the years, I’ve really seen the field develop. Pharmacokinetics was first used in the clinical environment. Then, it moved into the early clinical drug development, then the pre-clinical arena, and finally drug discovery. The use of pharmacokinetics was then based primarily on empirical observations. Over the past decade, mechanistic, physiologically based methodology has moved in the reverse direction, from the pre-clinical arena into the clinical arena and through to the regulatory process. Eventually, we will see mechanistic PK/PD become a standard best practice in informing patient care.
I look forward to being around for many, many more years making this happen. That would give me great satisfaction.
Chatting with a pharmacometrics thought leader
I’d like to thank Prof. Rowland for pulling up a seat at the Roundtable and sharing his insights with us. Learn more about his work at the University of Manchester Pharmacy School.
At Certara, we are passionate about empowering our customers with biosimulation and regulatory writing solutions to help them solve the toughest drug development problems. I hope that you’ll read our white paper “Integrating Regulatory Writing and Biosimulation into the Drug Development Process.” Let me know what you think in the comments section.