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- Clinical Physiology of the Kidneys
-
1. Molecular basis of genetic renal diseases 1
- Dr. Paul Jennings
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2. Molecular basis of genetic renal diseases 2
- Dr. Paul Jennings
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3. Assessment of renal function
- Dr. Jochen Raimann
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4. Isolated microhematuria and proteinuria in adults
- Dr. Eva Seiringer
-
5. Intradialytic oxygen saturation
- Dr. Lili Chan
-
6. Pervasive sensing in chronic kidney disease
- Ms. Maggie Han
- Ms. Schantel Williams
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7. The genetic basis of kidney cancer
- Dr. W. Marston Linehan
- Glomerular Disorders
-
8. Focal segmental glomerulosclerosis
- Prof. Moin Saleem
- Tubular Interstitial Disorders
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9. What’s new for IgA nephropathy part 1: epidemiology and pathogenesis
- Prof. Maurizio Salvadori
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10. What’s new for IgA nephropathy part 2: clinical presentation, diagnosis, prognosis, treatment
- Prof. Maurizio Salvadori
-
11. Renal complications of sickle cell disease
- Dr. Claire Sharpe
- Acute Kidney Injury
- Chronic Kidney Disease
-
13. Pathophysiology of acute renal failure
- Dr. Viviane Calice-Silva
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14. Anaemia in chronic kidney disease
- Prof. Iain Macdougall
-
15. Kidney disease and pregnancy: a new era?
- Dr. Kate Bramham
- Renal Cell Carcinoma
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16. The genetics and genomics of familial renal carcinoma
- Prof. Eamonn Maher
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17. Immune checkpoint blockade in renal cell carcinoma
- Prof. David McDermott
- Pharmacology and the Kidney
-
19. Toxicology of the kidney
- Prof. Lawrence Lash
- Proteomics and the Kidney
-
20. Proteomics in diabetic kidney disease
- Prof. Peter Rossing
-
21. Urinary proteomics in kidney and cardiovascular disease
- Prof. Harald Mischak
- Pediatric Nephrology
-
22. Continuous renal replacement therapy (CRRT) in children
- Prof. Timothy E. Bunchman
- Archived Lectures *These may not cover the latest advances in the field
-
23. Proteomics in kidney disease: clinical considerations
- Prof. Peter Rossing
Printable Handouts
Navigable Slide Index
- Introduction
- The therapeutic window
- Therapeutic window of factor Xa inhibitors
- The emerging discipline of pharmacometrics
- Importance of pharmacometrics as a tool
- Pharmacometrics in drug development
- Challenges of studies in CKD patients
- Case study 1: saxagliptin (onglyza)
- Clearance of saxagliptin and 5-hydroxy saxagliptin
- Saxagliptin data from study
- Pharmacometric approach to quantify exposure
- CKD/CRRT effects on saxagliptin exposure
- Simulation in ESRD patients (without CRRT)
- Simulation in CKD patients (saxagliptin)
- Simulation in CKD patients (metabolite)
- Projected AUC ratio
- Saxagliptin dosage information
- Case study 2: entecavir (baraclude)
- Entecavir data from study
- AUC without dose adjustment
- Relative reference range without dose adjustment
- AUC with dose adjustment
- Relative reference range with dose adjustment
- Entecavir dosing information
- What did we learn/impact?
- Case study 3: IBKM in adults
- Individual bayesian (urea) kinetic modeling
- IBKM uses blood and dialysate data
- IBKM calculates urea concentrations
- IBKM characterizes relationship
- Novel hemodialysis modalities
- IBKM can project effects of modality switch
- Case study 4: IBKM in pediatrics
- HD adequacy and nutrition status
- IBKM facilitates fine-tuning prescription
- Summary
Topics Covered
- The therapeutic window
- The emerging discipline of pharmacometrics
- Challenges of studies in CKD patients
- Pharmacometrics approaches in sexagliptin treatment
- Pharmacometrics approaches in entecavir treatment
- Individual bayesian kinetic modeling (IBKM)
- IBKM in adults
- IBKM in pediatrics
Links
Series:
Categories:
Therapeutic Areas:
Talk Citation
Pfister, M. (2014, December 4). Pharmacometric approaches to optimize use of drugs and dialysis treatments in patients with chronic kidney disease [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved November 24, 2024, from https://doi.org/10.69645/BXKI2724.Export Citation (RIS)
Publication History
Financial Disclosures
- Dr. Marc Pfister has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
Pharmacometric approaches to optimize use of drugs and dialysis treatments in patients with chronic kidney disease
Published on December 4, 2014
30 min
A selection of talks on Gastroenterology & Nephrology
Transcript
Please wait while the transcript is being prepared...
0:00
This is a talk for
the Henry Stewart Collection.
I'm Marc Pfister, a
trained nephrologist.
I worked in Switzerland and in
the US, in California at UCSF,
before I joined a couple of
pharmaceutical companies.
And now I work as
Chief Medical Officer
for a global consulting company.
The topic of this lecture is
"Pharmacometric Approaches
to Optimize Use of Drugs
and Dialysis Treatments
in Patients with
Chronic Kidney Disease."
0:36
Before we go to a
couple of case studies,
I want to briefly review the
concept of therapeutic window.
The goal of every
treatment in our patients
is to improve, extend, save lives.
So the goal is to optimize the
dosing so that patients have
maximum benefit and minimal risk
for adverse events, safety events.
To obtain that goal, we need to
understand the exposure range,
the concentration range for
a given drug and treatment.
And the goal is to have a maturity
of patients with this exposure
range so that, again, we can
optimize benefits and minimize
the risk for adverse
events for these patients.
And that range of
target concentrations
is called therapeutic window.
1:33
This is an example from
the cardiovascular space.
This plot shows a blue
line and a red line.
It compares a new class of drugs
to prevent thromboembolic events,
Factor Xa inhibitors, and compares
this new class with a standard
of care, which is
Enoxaparin, which is
shown as a black horizontal line.
The goal is to optimize dosing
for this new class of drug
so that the blue and the red
line are below the black line.
The blue line represents
thromboembolic events.
So the lower the number, the better.
That means more thromboembolic
events were protected.
The red line is
increasing with dose.
That is, the safety curve.
The higher dose, the
more bleeding events.
The same goal here is to have
this red line at the low level.
We can see that there is a window
in the middle where both the blue
and the red line are
below the black line.
So that means for
this class of drug,
there is a dose range that is
associated with better efficacy.
The blue line is
below the black line.
And also, better safety.
And that is the therapeutic
window for this class of drug.
And this plot is based on data
from a hundred different trials.
So the goal is with
pharmacometric approaches
to integrate data
from different trials
and to quantify this therapeutic
window so that we can compare
different compounds
and different doses
and optimize treatment for patients.
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