University of Groningen
Understanding individual drug response variation
Kroonen, Marjolein
DOI:
10.33612/diss.127010643
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Publication date: 2020
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Kroonen, M. (2020). Understanding individual drug response variation: Pharmacokinetic analysis of diabetes trials. University of Groningen. https://doi.org/10.33612/diss.127010643
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1
Introduction and aims
Published in adapted form
M.Y.A.M. Kroonen,
H.J. Lambers-Heerspink,
D. de Zeeuw;
In: (Clinical) Trial and Error
in Diabetic Nephropathy,
J.J.Roelofs, L.Vogt, (2019)
Status of trials in nephrology
Relatively low number of clinical trials in the field of nephrology
The landscape of clinical trials in general faces considerable challenges. Attrition rates in late stages of drug development are increasing along with a continuous rise in drug development costs. (1,2)
A concerted effort is necessary to find out how to develop new effective and safe drugs in an efficient and cost-effective way.
The area of nephrology, does not only suffer from the general problems faced in clinical trials, but also holds a number of other specific problems among which the smaller number of clinical trials in comparison to other specialties [Figure 1], most trials were too small to detect a realistic treatment effect, and sub-optimal quality of most trials. (3)
Figure 1. Number of published randomized controlled trials (RCT) in nephrology and twelve other specialties
of internal medicine from 1966 to 2002. (4)
Factors contributing to the low number of clinical trials in nephrology include the lack of visibility, lack of availability of new or more effective drugs, and the availability of patients willing to participate in clinical trials. (5-8) However, these low numbers do not adequately reflect the urgent need for new treatment strategies in nephrology.
Chapter 1
12
Chronic kidney disease is a large public health problem
The number of people requiring dialysis for end-stage renal disease (ESRD) has been increasing rapidly across the world. (9) This increase closely parallels ongoing growth in the prevalence of diabetes for which it is estimated that the number of diabetic patients will increase further from 415 million in 2015 to 642 million by 2040. (10) Chronic kidney disease (CKD), in particular when advanced stages are reached, is associated with a high risk of premature mortality, has a huge impact on the quality of life of patients and their relatives, and places a heavy burden on national health care budgets. (11,12) The high numbers of affected patients would suggest a high awareness to develop and test new interventions and thus a high number of clinical trials. Instead the opposite is seen. However, new interventions are highly desired, particularly since the current guideline recommended strategy of targeting the renin– angiotensin–aldosterone system (RAAS), is of proven benefit in preventing and treating diabetic nephropathy for some patients, but by far not for all. (13,14)
Successful trials
Trials in the past decades of nephrology research have provided insights in the targets to treat patients with diabetes mellitus type 2 and nephropathy. Some trials have shown that tight glycemic control has delayed the onset and progression of nephropathy in patients with diabetes mellitus type 1 and 2. Blood pressure lowering, in particular with ACE-inhibitors or Angiotensin Receptor Blockers, have also been shown to delay the onset of ESRD in patients with type 2 diabetes and CKD. (15,16) Analyses from trials with ARBs have also provided more insight in the importance of albuminuria lowering as an additional target for treatment. (17,18)
Residual risk
Despite the promising and successful results from optimal RAAS inhibition in
combination with tight glycemic and blood pressure control, many patients with diabetes and nephropathy still progress to ESRD. (13) The high residual risk is illustrated by the fact that the reduction of end-stage renal disease in the RENAAL was only 28% and not 100%. (19) In itself, this 28% is a considerable risk reduction compared to conventional therapy. Yet, the starting absolute risk in this population was substantial and thus a high residual risk remains despite the large risk reduction. (Figure 2)
New drugs and new targets
The identified high residual risk requires new targets and therapies. Several options were tested: Further lower the known risk markers by increasing the inhibition of the RAAS with existing and with new drugs; further lower the known risk markers by new interventions targeting novel target and pathophysiological pathways.
Figure 2. Renal risk reduction in two renal outcome trials RENAAL (losartan) and IDNT (irbesartan) in
comparison with treated cancer (1996-2003; US Cancer Institute Surveillance Epidemiology and End Results database). The Y-axis indicates death with the assumption that in the absence of dialysis or renal
transplantation, patients with end-stage renal disease would die. RAS = renin-angiotensin-system. Summarizes the residual renal risks after interventions in the IDNT and RENAAL trial. (20). These data highlight the need for additional therapies that further lower the risk of ESRD. Ongoing research has focused on the discovery of new drugs and targets that lower renal risk markers on top of established treatments.
Increasing RAAS-inhibition
RAAS inhibition with mono-therapy has been shown to be renoprotective in patients with diabetes and nephropathy. The next step was to inhibit the RAAS more stringently by combining existing therapies in an effort to further lower blood pressure and albuminuria. Unfortunately, the trials demonstrated no additional benefit of more stringent RAAS blockade either with combination of ACE-inhibitors and ARBs or combination of direct renin inhibition as adjunct to ACE-inhibition or ARBs. In fact, combination therapy was associated with a higher risk of hyperkalemia and acute kidney
Chapter 1
14
injury in all trials. Accordingly, current guidelines discourage the use of combination RAAS therapy.
New drugs same targets
New treatments to further lower albuminuria on top of single RAAS blockade were also discovered in the last decade. Sulodexide is one of these new treatments. Several studies showed that this drug lowered albuminuria on top of ACE-ARB by an allegedly effect on the glycocalyx, (a thin gel like layer covering the endothelium). (21-25) However, two large trials failed to demonstrate benefits on a surrogate outcome (albuminuria reduction) ESRD. The endothelin system is another promising target that has been targeted. Avosentan and atrasentan are examples of drugs that antagonize endothelin receptors. These agents marked promising results in their potential to lower blood pressure and albuminuria on top of RAAS inhibition in phase 2 trials. (26,27) These promising results led to large outcome trials such as the ASCEND, a trial in which the endothelin antagonist avosentan was studied in a clinical trial randomizing 1392 subjects to receive 25mg or 50mg avosentan or placebo. The ASCEND trial was terminated early because of safety issues particularly congestive heart failure due to the sodium retaining effects of endothelin antagonists. (28) However, the important lesson from the ASCEND trial was that a very specific endothelin receptor antagonist should be used to minimize the sodium retaining effects and mitigation strategies (such us diuretic use and selection of patients not prone to fluid retention) should be implemented. These strategies were implemented in the SONAR trial. The trial showed indeed that the endothelin receptor antagonist atrasentan showed a marked renoprotective effect with markedly lower incidence of heart failure compared to the ASCEND trial.(29)
New targets
Inflammation and oxidative stress emerged as important pathophysiological pathways that accelerate the development and progression of diabetic nephropathy. This knowledge has led to the development of specific anti-inflammatory anti-oxidative modulator such as bardoxolone methyl. (30) A phase 2 study with this agent demonstrated that bardoxolone causes a sustained increase in eGFR.
These promising results led to the design of a large outcome trial, designed to confirm the efficacy of bardoxolone methyl in 2185 patients with type 2 DM and CKD stage 4.
However, this study had to be terminated early again because of increased rates of congestive heart failure and mortality in the bardoxolone methyl arm.
Reason for these failed trials
The above summary is disappointing. None of the trials mentioned above have been able to identify a single new and effective treatment strategy for patients with diabetes and nephropathy despite the enormous human and financial resources that have been put into these large trials. Several important trial design elements may explain why the trials did not lead to the desired outcomes. It is unlikely that the trial endpoint and trial population were inappropriate since the endpoints and population were similar as the successful RENAAL and IDNT trials in the early 2000s. However, post-hoc analysis of these trials showed that in almost all trials lack of effect on the good risk markers (those leading to a good outcome) and/or too much effect on bad risk markers (those leading to poor outcomes) played an important role in the failure of these trials as summarized in Table 1.
For example, in a post hoc analysis of the ALTITUDE trial, it was shown that although aliskiren decreased blood pressure and albuminuria, there were still many patients in the aliskiren treatment arm who did not have a reduction in albuminuria. Moreover, patients with a robust lowering in albuminuria (i.e. >30% reduction) during the first six months of treatment had a significantly lower risk compared to patients in whom albuminuria did not change. (37) This suggests that if only these albuminuria responder patients were selected, the outcome of the trial would have been highly positive.
A similar situation was seen in the BEACON trial which was terminated after 9 months because of high rates of congestive heart failure and mortality. (36) However, exclusion of patients at high risk of congestive heart failure by selecting a population with a low BNP level (<200 pg/mL) and without a history of congestive heart failure gave a completely different picture. In this selected population, bardoxolone methyl actually did not increase the risk of congestive heart failure and may even offer renoprotection. (38) Selecting the right patient who thus tolerates the drug and beneficially respond to the drug is a key design element to conduct more efficient trials.
Chapter 1 16 Ta ble 1. O ve rv ie w o f fa ile d t ria ls Tr ia l T ype St ud y a rm s P ri m ar y o ut co m e Re sul t F ai lur e O NT A RGE T (3 1) (n = 2 5 6 20 ) DM 1& 2 T el mis ar ta n ve rs us Ra m ip ril ve rs us C omb in at io n Dia ly si s, DS C R, de at h. T he n umb er o f ev en ts fo r t he c omp os ite p rima ry ou tc om e w as s im ila r fo r t el m is ar ta n ( n= 11 47 [1 3· 4%] ) a nd r am ip ril (1 15 0 [ 13 ·5 %] ; h aza rd ra tio [H R] 1 ·0 0, 9 5% C I 0 ·9 2– 1· 09 ), b ut w as in cr ea se d w ith c omb in at io n t he ra py (1 23 3 [1 4. 5%] ; H R 1 ·0 9, 1 ·0 1– 1· 18 , p = 0· 03 7) . E ffe ct o n su rr oga te b ut hi gh S ide e ff ec t SU N -M AC RO (3 2) (n = 1 24 8) DM 2 Su lo de xi de ve rs us Pl ac eb o bo th o n t op o f RAA S b lo ck ade D SC R, E SRD , o r se ru m c re at in in e 6 .0 m g/dl. T he s ul ode xi de gr ou p h ad a lo w er n um be r of pr ima ry e ndp oi nt s. B ut c omp ar is on w as n ot st at is tic al ly s ign ific an t ( ha za rd r at io : 0 .8 5 [ 95 % co nfide nc e i nt er va l: 0 .5 0– 1. 44] ; P = 0.54 ). N o e ff ec t o f su rr oga te T RE AT (3 3) (n = 4 03 8) DM 2 Da rb ep oe tin -α ve rs us Pl ac eb o E SRD , de at h o r a ca rdi ov as cu la r ev en t D ea th o r a c ar di ov as cu la r e ve nt (h aza rd r at io f or da rb ep oe tin a lfa v s. p la ce bo , 1 .0 5; 9 5% co nfide nc e i nt er va l [ C I] , 0 .9 4 t o 1 .1 7; P = 0 .4 1) D ea th o r e nd -s ta ge r en al di se as e i n da rb ep oe tin al fa v s p la ce bo g ro up (h az ar d r at io , 1 .0 6; 9 5% C I, 0 .9 5 t o 1 .1 9; P = 0 .2 9) . E ff ec t o n su rr oga te b ut hi gh s ide e ff ec t
ALT IT U D E (3 4) (n = 8 56 1) DM 2 Al is ki re n Ve rs us Pl ac eb o bo th o n t op o f RAA S bl oc ka de E SRD , D SC R, de at h o r t im e t o ca rdi ov as cu la r de at h / fir st oc cu rr en ce o f ca rdi ac a rr es t Aft er a m edi an fo llo w -u p o f 3 2. 9 m on th s, th e pr im ar y e nd p oi nt h ad o cc ur re d i n 7 83 p at ie nt s (1 8. 3% ) a ss ign ed to a lis ki re n a s c om pa re d w ith 73 2 ( 17 .1 % ) a ss ign ed to p la ce bo (h aza rd r at io , 1. 08 ; 9 5% c on fide nc e i nt er va l [ C I] , 0 .9 8 t o 1 .2 0; P = 0 .1 2) . Lo w e ff ec t o n su rr oga te b ut hi gh s ide e ff ec t VA N E P H RO N D (3 5) (n = 1 44 8) DM 2 Lis in op ri l ve rs us Pl ac eb o B ot h o n t op o f lo sa rt an E SRD , de at h o r t he fir st o cc ur re nc e o f a c ha nge in th e es tim at ed G F R, o r. C om bi na tio n t he ra py o ff er ed n o r en al b en efit bu t r es ul te d i n e xc es si ve ris k o f h yp er ka le m ia (6 .3 v er su s 2 .6 e ve nt s p er 10 0 p er so n y ea rs ; P < 0 .0 01 ) a nd a cu te k idn ey in ju ry (12.2 ve rs us 6. 7 e ve nt s p er 1 00 p er so n y ea rs ; P < 0 .0 01 ). Lo w e ff ec t o n su rr oga te a nd hi gh s ide e ff ec t B E AC O N (3 6) (n = 2 18 5) DM 2 B ar do xo lo ne m et hy l v er su s Pl ac eb o E SRD , o r de at h fr om c ar di ov as cu la r ca us es . pr im ar y c om po si te o ut co m e ( ha za rd r at io in th e ba rdo xo lo ne m et hy l gr ou p v s. th e p la ce bo gr ou p, 0 .9 8; 9 5% co nfide nc e i nt er va l [ C I] , 0 .7 0 to 1 .3 7; P = 0 .9 2) De at h fr om c ar di ov as cu la r c au se s o cc ur re d i n 2 7 pa tie nt s r an do m ly a ss ign ed t o b ar do xo lo ne m et hy l a nd in 1 9 r an do m ly a s ign ed t o p la ce bo (h aza rd r at io , 1 .4 4; 9 5% C I, 0 .8 0 t o 2 .5 9; P = 0.23) E ff ec t o n su rr oga te a nd hi gh s ide e ff ec t AS C E N D (2 8) (n = 1 39 2) DM 2 Av os en ta n 25 m g/5 0 m g ve rs us Pl ac eb o Al l gr ou ps o n to p of RAAS bl oc ka de D SC R, E SRD , o r de at h. Av os en ta n r edu ce d p ro te in ur ia c om pa re d w ith pl ac eb o, b ut , h ad e xc es s adv er se c ar di ov as cu la r ev en ts ; e sp ec ia lly flu id o ve rlo ad ( 4. 6%; P = 0.225 ), co nge st iv e he ar t fa ilu re (3 .6 %; P = 0 .1 94 ) an d de at h ( 2. 6%) . E ff ec t o n su rr oga te b ut hi gh s ide e ff ec t
Chapter 1
18
Variability in drug response
Although the above examples are post-hoc analyses and are prone to bias and confounding, they illustrate that the design of the clinical outcome trials in diabetic nephropathy should pay more attention to the individual response of patients to existing and new drugs. In fact, response variation may play a much bigger and more important role than we thought in clinical trial design and appropriate attention to it may be a game changer when it comes to the design of new trials (i.e. personalized medicine).
Personalized medicine has been embraced in the oncology trials. Targeted therapies and careful patient selection based on genetic or biomarkers is common practice as illustrated by numerous examples. (39-41)
The nephrology area should follow the example from the oncology area and start selecting (and excluding) patients for trial enrollment who either do not tolerate the drug or who do not respond to the drug. The aforementioned SONAR trial is a first step in this direction. The design of the trial was such that patients are selected for trial participation based on their response to the drug. In this trial all patients received the endothelin receptor antagonist atrasentan for six weeks. Patients in whom albuminuria decreases by more than 30% (responders) and in whom there are no signs of sodium retention (e.g. no increase in body weight) were randomized to treatment with atrasentan or placebo. The trial demonstrated a marked renoprotection and a small increase in incidence of heart failure. Ongoing analyses from this trial will evaluate the usefulness and utility of the enrichment design both in terms of efficacy and safety.
A better understanding of the factors involved in the variability in response is needed to implement personalized medicine in clinical trials as well as in clinical practice. Drug response variation can be caused by variations in the genetic background of an individual that affect the drug target. For example, genetic variations in the ACE gene may affect disease progression and response to ACE-inhibitors and ARBs. Indeed, in clinical trials with these agents it has been shown that the ACE polymorphism DD genotype is associated with a faster disease progression and a more favorable response to ACE inhibitors (enalapril or ramipril) and the ARB losartan. (42,43)
Response variation may also be caused by between individual variations in systemic exposure to a drug which may be the consequence of underlying variations in absorption, distribution, metabolism or excretion. Previous studies focus on the relationship between drug dose and drug exposure with pharmacodynamic responses on a population level. Such studies investigate the optimal dose with optimal efficacy and minimal side effects on a population level but do not investigate the balance between efficacy and safety in individual patients and to what extent this varies among patients. There is thus a paucity of data in patients with diabetes and chronic kidney disease on the relationship between individual drug exposure and individual treatment response.
A better understanding of the between individual variability in drug exposure and pharmacodynamics response is needed followed by exploration of factors that determine the individual exposure. This will pave the way for specific interventions and strategies to optimize individual drug response with the ultimate aim to more efficiently design clinical trials and use drugs in clinical practice.
Research aims of this thesis
The important lessons learned from a decade of clinical trial failures in nephrology is that the one size fits all approach does not fit everyone. Accordingly, much more emphasis should be placed on the individual and how the individual responses to the prescribed drugs. As described above, various studies have investigated which clinical characteristics are involved. However, there are only few studies that systematically investigated to what extent individual drug exposure determines individual drug response in patients with type 2 diabetes. Therefore, the studies conducted in this thesis were designed to better understand the individual variation in drug response by investigating the role of individual drug exposure to various drugs registered for clinical use in patients with diabetes.
In Chapter 2 we aimed to investigate how the renal clearance (CLr) and apparent non-renal clearance of metformin (CLnr/F) in patients with varying degrees of kidney function influenced metformin exposure. This was performed in order to develop a dosing algorithm to tailor recommendations for patients using metformin.
Chapter 1
20
In Chapter 3 we aimed to explore the exposure-response relationship for atorvastatin and rosuvastatin for LDL and UPCR. The PLANET trials randomized patient with a urine-protein to creatinine ratio (UPCR) of 500-5000 mg/g and a fasting LDL-cholesterol >2.33 mmol/L to a 52-week treatment period with atorvastatin 80 mg, rosuvastatin 10 mg or rosuvastatin 40 mg and showed that atorvastatin but not rosuvastatin was able to reduce UPCR at similar LDL lowering properties. The individual changes in both UPCR and LDL-cholesterol during treatments with these statins varied widely between patients. This inter-individual variability could not be explained by patients’ physical or biochemical characteristic. Therefore, we aim to assess whether the plasma concentrations of both statins are associated with LDL-cholesterol and UPCR response.
In Chapter 4 we aimed to investigate the exposure-response relationship for the sodium glucose co-transporter 2 inhibitor dapagliflozin for renal risk markers. Dapagliflozin has been shown to decrease various renal risk markers such as HbA1c, systolic blood pressure, body weight and albuminuria in patients with diabetes mellitus type 2. Prior studies have confirmed that the response in these renal risk markers is variable between patients but reproducible upon re-exposure. Suggesting the response to dapagliflozin is a true pharmacological response rather than a random response variation. We aimed to explain the response variability in the different renal risk markers to the exposure of dapagliflozin.
In Chapter 5 we aimed to explore the exposure-response relationship in albuminuria for empagliflozin, linagliptin and telmisartan. To evaluate this exposure response relationship where we define exposure as (AUC0-∞) we sampled according to an additional
pharmacokinetic protocol in the ROTATE-2 trial. In this trial, patients with diabetes mellitus type 2 and elevated albuminuria were randomized to 4 different albuminuria lowering treatments.
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