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We continue our Norwegian Scientist series this month with an interview from Anders Åsberg, a very well-known name in the IATDMCT ‘microcosm.’ It’s really great to hear from Anders as one of the leaders in the field, who has always been swift to implement innovations in the TDM and clinical pharmacology space, to the benefit of patients. Apart from applying model informed dosing and using microsampling devices clinically, which Anders and his team are known for, it was great to hear about a novel approach to accurately determine GFR using serum iohexol concentrations (with a free shiny application, reducing the sampling time frame), as well as Anders’ dedication to research students. Anders was very kind to join us on a recent Eight Drugs a Week podcast episode to chat about some of the highlights of the upcoming congress. We’re looking forward to hearing more about his work in Oslo!
Anders Åsberg
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Can you tell us a little bit about your respective roles? What is a typical day like for you?
I have several ‘official’ responsibilities in my work, but all taken together research is the main activity. I am employed by Oslo University Hospital, Rikshospitalet, as head of the Laboratory for Renal Physiology and in that position, I also have an overreaching ‘control’ of the research activates of the Transplantation Nephrology Section. At the hospital, I am CEO for the Norwegian Renal Registry, a national quality registry for patients with severe renal disease, such as those in dialysis or kidney transplant recipients. I also have a 20% professor position at the Department of Pharmacy at the University of Oslo where I am a part of the Pharmacokinetic research group (PK-group) and teach pharmacy students in pharmacotherapy and pharmacokinetics.
A typical day starts with a short bike ride to Rikshospitalet at 07:00 to participate in the clinical morning meeting in which I try to give input on PK and drug dosing issues. Then there are e-mails, e-mails and e-mails, and many meetings to keep the different studies running smoothly and the laboratory to work well. I do not have any dedicated clinical responsibilities, but I use our tacrolimus popPK model to calculate AUC’s and give dose suggestions for selected patients. Our section and the university-based PK group are quite productive, so I get plenty of manuscripts and master- and PhD- theses to read. Several times a week there are also nephrologists or researchers from all over Norway that require data from the renal registry, and I prepare reports for them. I have an open-door policy so collaborating partners and PhD-students come to discuss projects quite regularly.
The day at the hospital usually ends at 17:00, but if there is feedback to PhD-students that I have not had time to attend during the day, I try to get it done before bedtime. Speedy feedback to PhD-students is one of the things I am trying hard to uphold, something I appreciated much from my supervisor professor Anders Hartmann.
Is there anything that your laboratory does, or that is done at your hospital/centre, that you would consider innovative?
We have start implementing capillary microsamples for tacrolimus monitoring in the clinic, which is a nice offer to the patients. We have also concluded a PK interaction study where patients take most of the samples themselves, which really make this kind of detailed PK investigations easier, and cheaper, to perform.
We perform measured GFR investigations using the iohexol serum clearance method at our lab. Previously we were not able to perform it in patients where it might be most useful, i.e. those with low renal function, since the last sample had to be taken after 8 or 24 hours, and often the patient would have already left the hospital by then. By using a popPK model and sampling in the distribution phase we can now determine measured GFR with high accuracy within 5 hours, also in people with low renal function (free Shiny app: mgfr.no). This now allows us to perform the investigation in all patients, including those with low GFR and living long distance from the lab.
What technological innovations have entered into use during your career that have permitted a change, or evolution, in practice?
The development in drug analyses have been quite drastic if you look over the whole period I have worked within the field. Now being able to measure immunosuppressive drug concentrations in small blood samples and also in isolated cells and different tissues is quite amazing.
When I first started with population PK modeling the computer power was not good enough to really perform relevant non-parametric models. This has drastically changed and now a standard laptop is capable to run most of these models. With super-computers the possibilities are amazing. Linked to this, I think the development in machine learning and artificial intelligence is interesting and potentially opens a wide range of new possibilities.
How did you become interested in your area of expertise?
Since I was first introduced to pharmacokinetics during my pharmacy training it has been a favorite field of interest. For my Masters, I was part of a PK interaction study and since then it has been my main focus area. I was later introduced to popPK modelling and realized that this would potentially be a very valuable tool for clinicians but that adaption to the user interface would be required for wider use.
Is there anything that you’ve seen or heard about recently and thought “I’d like to incorporate that idea at my center”?
The latest big thing is AI/ML, I think. Using this to get good prediction of future events I think is a promising field of research. For example, being able to predict future renal function in our renal transplant recipients would be a great tool for better individualization of their therapy.
What sort of research do you have on the horizon that you think might influence clinical practice in the future?
Together with Ida Robertsen and her team in the PK group at the university of Oslo we are looking into what information the microbiome can help us with regarding drug dose individualization. We also collaborate with Jean-Baptiste Woillard et al in Limoges on AI: very exiting results there. Lastly, we are trying to create a sort of ‘95% CI’ for the AUC predictions from LSS (non-parametric models). I think this is important for an even better implementation of computer dosing tools in the clinic.
What do you consider is the future for TDM and CT? What are you excited about? What are the challenges we face?
Personalized medicine is in my mind a topic that has been ‘stolen’ from us by the ‘right drug to the right patient’ people. It’s a bit annoying how they have been much more successful than us in the TDM field to get the information out broadly! If we cooperate, there should be a place for both: finding the right drug AND the right dose of that drug for each patient. Joined forces is probably the way to go and this will be a major advantage to patients. With the available computer tools that we have today, and those that will become available in the near future, together with sampling by the patients themselves at the most informative time points, I think we will see great improvement in target achievement.
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