By Yong-Bee Lim
The Post-Antibiotic Era Problem: What are the Issues, and How Can Adaptive Clinical Trials Potentially Help?
Nostalgia is a powerful thing. When people get nostalgic, they are cognitively living in the past; in this constructed past, the past seems rosy, and often conceived of as more positive than the present. That said, even with rose-tinted glasses, it is hard to argue that life (if defined as survivability) was better before the introduction of antibiotics. For example, mortality rates from pneumococcal pneumonia were 30-35% in the pre-antibiotic era, with the therapy often being quarantining patients. Antibiotics have allowed for both the morbidity and mortality rates of pneumococcal pneumonia to drop to nearly zero in developed countries. Furthermore, antibiotics allow procedures that would have been impossible in a pre-antibiotic era; organ transplants, invasive procedures, and intensive care units would not be possible without effective antibiotics.
A recent piece of news to hit the public health radar involves a man in New Zealand named Henry Pool. Pool, while teaching English in Vietnam, was operated on following a brain hemorrhage. When flown following the operation to a Wellington hospital, it was discovered that he carried a bacteria strain identified as KPC-Oxa 48: a strain of bacteria that is resistant to every antibiotic currently available to man. To contain the possibility of the strain of bacteria getting out, Pool was forcibly quarantined for 6 months until he passed away. 
This recent death in New Zealand highlights a threat that looms ever closer in the public health horizon: the post-antibiotic era. Due to a number of factors, including over-prescription of antibiotics to patients and over-use of antibiotics in farming and animal cultivation, bacteria have undergone evolutionary pressures to resist and overcome the mechanisms of our current arsenal antibiotics; several adaptations include the production of enzymes to modify antibiotics, cell wall changes that prevent the ingress of antibiotics inside the bacterium, and the creation of pumps to transfer antibiotics outside of the cell before the antibiotic’s effects are actualized. Furthermore, evidence points to the fact that multiply-resistant bacteria are not staying confined to hospitals as they traditionally have; certain bacteria such as Streptococcus pneumonia and Staphylococcus aureus with partial/complete resistance to penicillin have been detected in community populations.
The concept of antibiotic resistance is not a foreign one to scientists and individuals in the public health sector. Staphylococcus aureus was actually noted to have started developing antibiotic resistance to penicillin as early as the 1940s. Despite this knowledge that antibiotic resistance could, and would, develop over time, very little is available in regards to innovative new antibiotics to counter the rising threat of antibiotic-resistant bacteria. There has been “no major classes of antibiotics introduced” between the years of 1962 and 2000; furthermore, while representatives of novel antibacterial classes (linezolid: 2000, daptomycin: 2003, retapamulin: 2007) have been registered, the chemical classes from whence these representatives originate were patented or reported historically (oxazolidnones: 1978, acid lipopetides: 1987, pleuromutilins: 1952).
If the threat is realized, then, why is there such paucity in the development and production of novel and effective antibacterial therapies? Part of the equation has to do with the society we live in; money is important to companies. Over the past several decades, a number of large pharmaceutical companies have drastically cut funding and maintaining the internal capacity for R&D of antibacterial therapies. It is often argued that this decline is partially explained by the fact that pharmaceutical companies seek to shift R&D resources from antibacterial drug discovery programs to other, more profitable therapy areas such as musculoskeletal and central nervous system (CNS) drugs., The net effect of various economic barriers involved in the development of an antibiotic (if successful) is a net loss of $50 million dollars compared to a $1 billion gain for a new musculoskeletal drug at the time of discovery. In addition, mergers and take-overs of pharmaceutical companies often result in a restructuring of priorities and personnel; these restructures have often included the loss of research groups with expertise in antibiotic drug discovery.
So if part of the issue is economics, what can be done to better galvanize and incentivize pharmaceutical companies to come back and do R&D on antibacterial drugs? One area where companies often hemorrhage money is in the clinical trials necessary to prove both the safety and efficacy of a product. Oftentimes, the bulk of R&D funds are spent on clinical trials. Clinical trials (depending on the size of the sample needed to test the product, the cost of developing the product itself, and other factors) can run in the ballpark of $100 million dollars per trial; with a minimum of 3 phases of clinical trials (with a high probability of repeating at least one phase of a trial), it is easy to see a successful product would cost a minimum of $400 million dollars in clinical trials alone.
Under the current model of clinical trials, trials are clearly demarcated between phases (Clinical Phase 1, Clinical Phase 2, and Clinical Phase 3) that must be done in a sequential fashion. Furthermore, these trials are rigid in the fact that parameters may not be changed during the course of a trial; all participants must be kept throughout the trial, dosages may not be altered, and trials (except under certain circumstances) must be completed until the end. Among a number of situations, this lock-step approach inflates costs when observations might indicate:
– A certain subset is not responding to a dose (perhaps the dose is too low)
– The entire sample is not responding to the product (at any dose)
Using innovative, high-level Bayesian biostatistics, a new avenue of clinical research design is being explored that may help alleviate some of the costs of clinical trials. Adaptive clinical trials are specifically designed studies that are meant to “adapt” as a clinical trial proceeds; these adaptations occur through an analysis of the accumulated results in a trial. As opposed to the lock-step and rigid clinical trial structure that is currently used, adaptive clinical trials allow modifications to be introduced during the trial phase. These modifications could include, but are not limited to:
– Sample size re-estimation: If the number of people for a trial is too small or too large, this can be adapted during the trial.
– Early stopping of clinical trials: In the event that there is evidence that the product isn’t performing the way it is supposed to (lack of efficacy), trials can be shut down to save funds and resources.
– Dropping suboptimal groups: In the event that there is evidence that the product isn’t effective in a subgroup of the trial sample (perhaps a group with a low dose is not presenting results), then the group could be dropped to save funds and resources.
– Overlapping trials: Adaptive trials could overlap phases (the tail end of phase 1, for example, could overlap the beginning of phase 2), resulting in faster clinical trial completion and, hopefully, swifter licensure.
It should be noted that this type of approach is very new, and is only just garnering use in various areas that require clinical trials. For example, it has not been used, as of this post, for the development of Medical Countermeasures (MCMs). However, if it can be successfully executed, it holds possibilities in significantly cutting down both the temporal constraints, as well as the financial burdens, of attaining the novel and effective antibiotics that are necessary to help curb the growing antibiotic-resistant bacteria threat.
Perhaps the phraseology “post-antibiotic era” is too strong; it seems to evoke a sense of fear, and fails to address the idea that future innovations exist in the pipeline to potentially deal with issues of current levels of antibiotic resistance. However, what can be said is that we are starting to run out of options in our bag of tricks, and it will take more than a wave of a wand and an “abracadabra” to resolve this threat to the status quo: a public health era in which antibiotics work against bacteria to increase survivability. While there are multi-faceted issues contributing to this issue, the ability to help make antibacterial R&D more financially viable for pharmaceutical companies (through the use of innovations such as adaptive clinical trials) could help in dealing with this public health concern.
Yong-Bee Lim is a PhD student in Biodefense at George Mason University. He holds a B.S. in Psychology and an M.S. in Biodefense from George Mason University as well. Contact him at firstname.lastname@example.org or on Twitter @yblim3.
 Shai Ashkenazi. (2012). “Beginning and possibly the end of the antibiotic era,” Journal of Pediatrics and Child Health, 49 (3): pp. 179 – 182.
 RP Wenzel and MB Edmond. (2000). “Managing antibiotic resistance,” New England Journal of Medicine, 343: pp. 1961 – 1963
 “Kiwi dies with bug no drug could beat,” New Zealand Herald, accessed 11/23/2013: http://m.nzherald.co.nz/nz/news/article.cfm?c_id=1&objectid=11159413
 LF Chen, T Chopra, and KS Kaye. (2009). “Pathogens resistant to antimicrobial agents,” Infectious Disease Clinics of North America, 23: pp. 817 – 845
 “Methicillin-Resistant Staphylococcus aureus (MRSA),” National Institute of Allergy and Infectious Diseases, accessed 11/26/2013, http://www.niaid.nih.gov/topics/antimicrobialresistance/examples/mrsa/pages/history.aspx
 MA Fischbach and CT Walsh. (2009). “Antibiotics for emerging pathogens,” Science, 325: pp. 1089 – 1093
 Lynn L. Silver. (2011). “Challenges of antibacterial discovery,” Clinical Microbiology Reviews, 24 (1): pp.71 – 109
 S. Projan. (2003). “Why is big pharma getting out of antibacterial drug discovery?” Current Opinion in Microbiology, 6 (5): pp. 427 – 430
 R Finch and P Hunger. (2006). “Antibiotic resistance – action to promote new technologies,” Journal of Antimicrobial Chemotherapy, 58 (Suppl): pp. 3 – 22
 Priya Sharma and Adrian Towse. (2011). “New drugs to tackle antimicrobial resistance: Analysis of EU policy options.”
 I. Chopra. (2008). “Treatment of health-care-associated infections caused by Gram-negative bacteria: a consensus statement,” Lancet Infectious Diseases, 8: pp. 133 – 139
 “How the FDA Stifles New Cures, Part I: The Rising Cost of Clinical Trials,” Forbes, accessed 11/26/2013, http://www.forbes.com/sites/aroy/2012/04/24/how-the-fda-stifles-new-cures-part-i-the-rising-cost-of-clinical-trials/
 Donald A. Berry. (2010). “Adapative clinical trials: The promise and the caution,” American Society of Clinical Oncology, 29 (6): pp. 606 – 609