Thursday, December 5, 2013
Several weeks ago, Brad Spellberg and John Rex published a fascinating analysis of cost and benefits of a pathogen-specific therapy for highly resistant infections. They used carbapenem-resistant Acinetobacter baumannii as their case study. There are a couple of different ways of looking at this as I see it. First – how much is a so-called Quality life adjusted year worth? Apparently, the number accepted by most is something like $50,000. If that’s true, its hard to understand how cancer therapies that prolong life, frequently without much quality benefit, for a few months are worth up to $100,000. But maybe I’m missing something. That said – who decided that $50,000 is a correct price for a year of quality life? The other way of looking at this is based on overall cost savings to the healthcare system.
Based on these sorts of considerations, Spellberg and Rex clearly demonstrate that if therapy costs $10,000, the cost per quality life year is only $20,000 (much less than $50,000). At prices of $4-8000 per course there were clear savings in health care costs overall. In a sensitivity analysis, the authors show (Table below - click to enlarge), that even costs of therapy as high as $30,000, depending on the excess mortality caused by these resistant infections and the efficacy of the new therapy in preventing mortality, the costs could still be below $50,000 per quality year of life.
As I have argued previously, costs of antibiotics like the example chosen by Spellberg and Rex will have to be high in order to provide sufficient return on investment for the companies that market these products. Given the potential for this return on investment plus feasible regulatory pathways for getting to market, we can expect to see more and more large pharmaceutical companies like Sanofi and Roche getting back into the antibiotics field of research. With this movement, the private investment in antibiotics will once again flourish. So – overall – the development of these therapies is a win-win-win for patients, physicians, societies and private industry and their shareholders.
Saturday, November 23, 2013
One of the general problems with generic drugs is that many have been developed long ago when our understanding of medicine was not the same as it is today. Clinical trials were smaller making safety risks greater (since fewer patients are studied in a controlled manor). We had a lower appreciation for certain safety risks such as effects on the heart several decades ago.
In addition, our understanding of how drugs work and how to estimate how well they work has also changed over the years. In the case of antibiotics, the growth in importance of pharmacodynamics measures of activity has clearly been a major driver of our improved understanding of antibiotic efficacy and how to predict this in human trials. It affects our choice of dose and regimen and may inform decisions to stop development if the doses predicted to be efficacious by pharmacodynamics are too close to doses where safety risks become high.
How do these considerations impact the way we use generic antibiotics? Until now – not at all. In terms of safety, a label change for a generic drug would have to wait for action by the brand manufacturer before it could be reviewed by FDA. Of course, some label changes are initiated by FDA – but are still carried out through negotiations with the brand manufacturer. One wonders what happens when there is no such thing as a brand manufacturer anymore – like might be the case for penicillin (you remember penicillin, right?). A recent proposal by the FDA would allow a generic manufacturer to initiate such safety label changes and presumably would allow the FDA to initiate this with generic manufacturers as well. This gets around the restriction of having to work with a brand manufacturer when none exists, and provides more speed and flexibility to get safety labeling out to physicians and patients. All of this presumes that someone actually pays attention to these label changes of generic drugs – but that’s another problem.
I have already written several blogs on the problem of generic antibiotics in terms of relabeling for efficacy concerns (1,2). Mostly this has been related to generic drugs that were approved many years ago for the treatment of infections like sinusitis and bronchitis where the trials that were performed to prove efficacy are no longer accepted by either FDA or EMA today. These approvals are of greater concern today since a number of these drugs have had recent labeling changes (macrolides and fluoroquinolones) to highlight serious safety concerns. At the same time, modern branded antibiotics studied for the same infections have been forced off the marketplace for the treatment of those same infections because their trial designs were no longer acceptable for proving efficacy plus there were some safety concerns (although the safety concerns do not seem more serious to me than those for generics).
While I don’t see evidence of this changing, I do see the first crack in the door to relabeling for antibiotic efficacy at FDA. This is exemplified by the recent advisory committee meeting where relabeling of generic antibiotics (and new antibiotics for that matter) for susceptibility breakpoints was discussed. The meeting was summarized nicely by John Rex in this blog last week. Here, the FDA is the regulatory body that decides susceptibility breakpoints. As John notes – this is a very important decision directly impacting the efficacy of the antibiotic both in clinical trials and in the marketplace. The FDA is proposing to re-look at breakpoints through the lens of pharmacodynamics – a position supported generally by the advisory committee.
These efforts by FDA to reconsider generic labeling is an important step forward in that it will start to place modern, branded antibiotics and generics on a more level playing field. We just need the FDA to execute on these plans. The FDA also should reconsider the approval of generic antibiotics where the trial designs used to prove efficacy of those drugs are no longer considered valid. Either branded drugs should be allowed to seek approval with the same trial designs used to approve the generics, or the generics should have their approval for treatment of these indications removed from the label.
Tuesday, November 12, 2013
GUEST BLOGGER - JOHN REX
Dr. Rex is VP and Global Head of Infection Development at AstraZeneca Pharmaceuticals; a Non-Executive Director at F2G, Limited; and an Adjunct Professor of Medicine at the University of Texas Medical School-Houston.
PK-PD underpins both our development programs and interpretive breakpoints
On 17 Oct 2013, the FDA’s Anti-Infective Drugs Advisory Committee (AIDAC) met to discuss thechallenge of setting and updating interpretive breakpoints. For those new to the area, interpretive breakpoints are the rules used to provide predictive categories of Susceptible, Intermediate, or Resistant (S, I, and R) that give health care providers a quick guide to possible antibiotic choices.
On the surface, this sounds simple – does the drug inhibit the bacteria or not? But, the problem becomes complex very quickly. First, the idea of “the drug” has to be translated into “the concentration of the drug at the relevant body site when the patient is given a specific dosage regimen.” Second, the drug’s concentration in patients rises and falls with dosing whereas testing in the laboratory can only for practical purposes be done at fixed drug concentrations. Third, experience has shown that infections differ in terms of the intensity of drug effect needed. Finally, not at all body sites are the same in terms of drug penetration!
Despite this complexity it has been possible to develop breakpoints for most bug-drug combinations that offer a good aid to drug selection. But, the challenge that has emerged is that new information has emerged over the past 20 years that has shown us ways in which some of our breakpoints are suboptimal. Much of this insight flows from the science of PK-PD (pharmacokinetics and pharmacodynamics). We now have a clear understanding of how the shape of the drug exposure curve relates to effect of the bug and how to use preclinical in vitro and in vivo models to predict the required shape for clinical effect in man. We also have an understanding of ways to model the shape of the curve that deal with the fact that different individuals will have slightly different curves – we all clear drugs from our body at a different rate and have different volumes of distribution.
In addition, new insights into best ways to do the in vitro susceptibility test and the evolution of new mechanisms of resistance may have an impact on our view of the most appropriate breakpoint. Finally, some drugs have a sufficiently broad range of indicated dosages that a single set of breakpoints doesn’t seem appropriate, especially give rising rates of resistance and our limited new drug pipeline.
And finally, there was a critical need to address this because of a problem that has come out of the woodwork as we’ve begun to implement the streamlined development programs outlined by the 7 Nov 2013 release of the final version of the EMA addendum on antibacterial development and the July 2013 release of the FDA’s Unmet Need guidance.
These new approaches to development can collectively be described under the rubric of the tiered development approach that my colleagues and I recently described in our paper in The Lancet Infectious Diseases and will in most cases result in initial registration based on much more focused datasets than in the past.
But (and here’s the problem), small datasets almost invariably mean that isolates with the highest MIC in a drug’s treatable range will NOT be seen in the course of at least the initial development program. To understand this, see the figure at right showing the typical frequency distribution of MICs for wild-type (non-resistant) isolates of a any given organism vs. any given drug. Although the midpoint of the distribution may differ across various bug-drug combinations, the 4- or 5-log2 distribution of MICs is essentially universally seen and isolates with the highest MIC are uncommon.
Modern development programs will always focus on providing enough drug to treat even the highest MIC isolates. However, breakpoint setting has in the past required capture of at least one case of patient infected with the highest MIC isolate. Absent such experience, there has been a tendency to set breakpoints such the higher MIC isolates are categorized as either Resistant (R) or even more confusingly as Non-Susceptible (NS).
Whether labeled as R or NS, the practical consequence is that the drug’s use for these isolates will be effectively curtailed in practice. This is effectively an illogical Catch-22 — if we believe in PK-PD for support of our trial programs and registration, we should also trust it to help us set breakpoints.
In recognition of all of these challenges, the FDA convened this AIDAC and asked the committee to comment on two hypothetical cases constructed by the FDA to represent elements of this problem.
The outcome? Although the actual votes suggest a split views, it is important (as with all ACs) to listen not to the votes but rather to the logic behind them. Despite a range of Yes and No votes, there was actually near complete agreement that PK-PD really should be used to augment our approach to setting breakpoints. Presentations from multiple societies were supportive and the discussion by Advisory Committee really focused on the details of how this should be done rather than on whether it should be done.
A lot of the debate focused on the question of how finely we could adjust the guidance. Is it, for example, possible to have breakpoints that depend not just on the bug and drug, but also the site of infection? The committee on the whole felt this was too complicated to manage, especially as the laboratory can’t always infer the site of infection from the its knowledge of specimen (e.g., an organism found in the blood could relate to many different actual sites of infection). But, the AC did support the idea that PK (especially PK from patients) could be the basis for recommending dosage adjustments that would permit a single set of breakpoints to be applied across all indications.
All of this is, in my view, a really encouraging demonstration of how we are using science-based logic to enable the development of much-needed and potentially life-saving antibiotics prior to future epidemics of highly resistant bacteria.
John H. Rex, MD