The medical community continues to strive for advancements in diagnostic technologies, particularly those that can detect pathogens directly from blood samples. A recent session at ASM Microbe 2024 in Atlanta chaired by Linoj Samuel delved into the complexities and challenges that have hindered the integration of these technologies into clinical practice. Direct-from-blood pathogen detection technologies are designed to bypass traditional culture methods, which can be time-consuming and sometimes ineffective in identifying fastidious or non-culturable pathogens. By utilizing such tools, healthcare providers can obtain actionable information swiftly, allowing for the narrowing of therapy and de-escalation of antibiotics. This rapid turnaround is crucial in managing sepsis, where every hour counts in the race against mortality and morbidity.
The session highlighted a blend of technical and non-technical challenges, from the intricacies of sample preparation, pathogen detection to the broader implications for clinical decision-making. Dr. Valeria Fabre’s insightful presentation underscored the potential of these technologies to revolutionize patient care, offering a clinician’s perspective on their impact on treatment strategies.
Economically, the implementation of these technologies presents both challenges and opportunities. While initial costs may be higher due to equipment and workforce training, the potential for reducing the length of hospital stays, decreasing the use of broad-spectrum antibiotics, and preventing the spread of resistant pathogens lead to significant savings.
Key takeaways from the discussion emphasized the need for a deeper understanding of the goals behind direct-from-blood pathogen detection. What are the specific outcomes we aim to achieve? How can these technologies influence clinical decisions, patient outcomes, and the economic aspects of healthcare? The current absence of this information hinders assessment of the value such diagnostics bring and thus their adoption. While much of the current efforts are focused on nucleic acid technologies, the development of imaging and spectroscopy-based technologies adds to the diversity of diagnostic approaches, potentially offering complementary benefits to nucleic acid-based methods. These technologies may provide additional layers of information, that may not be available through nucleic acid testing, such as greater confidence in detecting the presence/absence of bacteremia and antimicrobial susceptibility information.
Overall, there is a palpable sense of optimism about the future. The next generation of pathogen detection technologies promises to address current technical limitations more effectively. However, the adoption of these technologies hinges on a much better understanding, and more importantly demonstration, of their value. Failure to take this into account during development and design of validation studies may inhibit their use in clinical settings, which would be a shame.
Isolating bacteria directly from blood or positive blood culture present a unique set of problems for clinical microbiologists and researchers. We are happy that multiple recent studies using our Separation Cartridge have performed very well in both applications. This post relates to the positive blood culture application.
One ongoing study at a local hospital has observed that traditional ID results could be obtained within a day (whereas without using the cartridge results have taken 2-5 days) and that the ID results obtained using the cartridge matches that obtained by subculturing.
The shorter time-to-result using the cartridge was because it eliminated the need for subculturing decreasing the time to ID & AST by at least 24 hours. While it is generally accepted that that direct testing of positive blood culture broths is feasible, results have been variable (for instance better success with Gram-negative rods (GNR) than Gram-positive cocci (GPC)), workflow sub-optimal, or the method too expensive.
Preliminary experiences indicate that the cartridge does not have these limitations. The process takes ≤ 5 minutes, requires no new instrumentation, and uses one buffer that can be easily sourced. Results have been consistent regardless of whether it is GNR / GPC. More studies are taking place at other hospitals and microbiology labs that we will keep you updated on.
If this is an area of interest to you or your organization, please contact us (www.3idx.com). We are interested in setting up demos and additional studies to assess performance in different settings and applications. Thank you.
A common refrain in this post-antibiotic era is that we need new antibiotics and new diagnostics . While the challenges of developing a new antibiotic are better acknowledged and understood, many are very surprised that we still use fundamentally the same procedure as used pre-WWII.
So, how is it that we are, at the start of 2020 and ~30 years since the dawn of the PCR-era, still talking about the need for better bacterial diagnostics? There are multiple technical and real-world challenges that continue to stymie the development of PCR-based tests such as speed, volume that can be processed, number of bacteria identified, and so on. Sensitivity and Specificity of a PCR-based test (or rather the lack of sufficient Sensitivity and Specificity) are two key performance attributes that have held back widespread clinical use of PCR-based tests. For this discussion, we focus on identifying bacteria directly from blood for guiding treatment of bloodstream infections, especially those that might lead to severe sepsis or septic shock.
Multiple PCR-based approaches are being developed to rapidly identify bacteria from blood. To a neutral observer it would appear that the reason we do not have a suitable bacteria test is because we have not developed a good enough PCR-based test. And that suitably optimizing such a test would solve the problem. Is this correct? Or are there some fundamental limitations that have held back clinical application?
In our opinion, the fundamental technical limitation is centered around the sensitivity of PCR-based tests and a fundamental practical limitation is centered around the ability to lower costs to a level that the healthcare system can support.
There are numerous text books and reviews providing a basis for determining the sensitivity and specificity of a test. Here is one. Briefly, Sensitivity refers to how good a test is at correctly identifying people who have the disease. While Specificity is concerned with how good the test is at correctly identifying people who do not have the disease.
What can we learn from these numbers for a bacterial diagnostic based on PCR? Let’s take the case of a hospital that analyzes 100,000 bacterial ID tests a year.
The percentage of samples that turn positive upon blood culturing ranges from 5 to 10%. Using the upper end of this range it means that out of the 100,000 samples submitted for bacterial ID tests, ~10,000 turn positive. [Note: This is frequently viewed as the number of samples that actually contain bacteria though there is widespread acknowledgment that culturing underestimates the number. More on this later. But, for the moment, since culturing is the gold standard (albeit an imperfect one) let’s go with 10,000 samples out of the 100,000 samples contain bacteria and therefore represent an infection.]
Data from two commercially available PCR based tests exhibit sensitivity and specificity are shown in the table below.
Sensitivity
Specificity
Septifast ®
42.9%
88.2%
SepsiTest ®
28.6%
85.3%
The sensitivity of these two tests range from 28.6% to 42.9%. In other words, if the PCR result came back negative (suggesting there is no bacteria), you could only be ~43% sure that there really was no infection! Think about that for a moment. If you were a physician making this decision, would you decide not to administer antibiotics based on this result? You’re most likely going to administer the antibiotics as you’re not that confident that you can rely on the negative result. Similarly, the specificity of these two tests range from 85.3% to 88.2%. In this case, you can be 88% sure that if you got a positive result, the patient has an infection though there’s a 12% chance that the result may not be accurate.
Let’s apply the above numbers to our hospital that processes 100,000 blood culture samples. Suppose that these samples are tested by a PCR-based test instead of being submitted for blood culture testing. Using the Sensitivity and Specificity numbers from above, this means that, of the 100,000 samples, 15,400 will yield a positive result. But, only 4,600 of these are truly positive. So, you will end up administering antibiotics unnecessarily for a large number of patients based on the 10,800 positive results. Similarly, you would have had 84,600 negative results of which 5,400 are false negatives. This means that you would have chosen not to administer antibiotics despite patients needing it.
“True” Result
Positive
Negative
PCR test positive
4,600
10,800
PCR test negative
5,400
79,200
As a physician or a hospital, the number of incorrect decisions resulting by relying on such a test is too high – jeopardizing patient safety. Does it really provide a significant benefit over the current practice where antibiotics are administered based largely on clinical judgment? At the present moment at least, the general opinion is no. Since it does not offer significantly helpful guidance relative to current practice it does nothing to correct overuse or misuse of antibiotics.
Most of the time when we consider how to use the result from a diagnostic test, we ask ourselves, if it yields a positive result would I know what to do next? That is an important question. But, in this application, it is equally (if not more) important to ask if the test yields a negative result, would I know what to do next? There is not sufficient data (and may never be) to guide treatment decisions when a PCR-based test is negative. This is the fundamental technical limitation.
Besides their performance, PCR-based tests also create problems due to their cost and operation. A single test costs $70 – $200 based on the number of bacteria identified. Using our example, if such a test were used for each sample currently submitted for blood culture, it would cost each hospital $7-$20 million (just in consumables). Which consumes a significant portion of a microbiology lab budget leaving little to no money for other tests. And still leaves a large number of bacteria unidentified!
In theory one can design a PCR test that is multiplexed to cover a large number of bacteria. But, this will increase the cost per test. Splitting the number of bacteria identified across multiple test panels is one way of covering a broader range. But, this takes away the advantages of cost reduction due to large volumes. How does one respond to new strains or species that are of urgent concern that was not anticipated? In different regions of the world? The modifications to the manufacturing process to address these different demands make it very challenging for the manufacturer to keep costs low.
So, at a fundamental level, PCR-based tests for identifying bacteria directly from blood face limitations due to poor performance, high costs, and appear to not aid decision-making or operational efficiency.
Significantly improving sensitivity and controlling costs are therefore necessary, but not sufficient, conditions for enabling widespread use of PCR as a bacterial ID test direct from patient sample. And until they are satisfactorily resolved, there will continue to be a reluctance in using such tests to guide antibiotic treatment.
Which means that we owe it to ourselves and all patients to consider and develop alternative ID techniques. It’s not that one technique is a winner and the other the loser in such an effort. The problem is large enough that multiple solutions will be needed. The more diagnostic options we have, the better we can aid physicians in making the best decisions for treatment while slowing the spread of antimicrobial resistant bacteria.
Antibiotics and focusing on infectious diseases is not the area where brainpower and money are focused on presently. It’s not as if people have suddenly stopped getting infections or that we don’t incur huge medical care costs because of them. Three infectious diseases were ranked in the top ten causes of death worldwide in 2016 by the World Health Organization. In the US, Among major disease categories, the cost per case grew fastest for infectious diseases.
Meanwhile the cost of treating patients who develop sepsis in the hospital rose by 20% in just three years, with hospitals spending $1.5 billion more last year than in 2015. In the US, the average cost per case for hospital-associated sepsis was slightly over $70,000 in 2018 with an annual increase in incidence of nearly 13%. Each year at least 1.7 million adults develop Sepsis and one in three patients who die in a hospital have Sepsis.
So, why the apparent lack of interest in tackling the problem? The challenges with new antibiotics development have been eloquently summarized by Isaac Stoner that I would highly recommend reading regardless of whether you are interested in this space or not. This captures the challenges faced by an antibiotic developer in achieving commercial success even if they have achieved technical success (i.e. a new antibiotic that works). Largely because of these struggles, many have concluded that antibiotics development carries too high a risk with very little return presently; one just has to wait until someone finds a way to make antibiotics profitable again.
Paradoxically, the situation, impact, and incentives work the other way for diagnostics. But this does not appear to have been fully appreciated by the broader audience yet. And recent “successes” have not delivered on expectations. But the case to persist is strong.
New antibiotics struggle to achieve commercial success because they are reserved for use as a last resort. This antibiotic stewardship, which is needed, limits the number of prescriptions for the new antibiotic making it difficult to achieve profitability. Having a diagnostic determine which antibiotic to administer (new or existing) promotes stewardship and reduces both overuse and misuse of antibiotics. If done right, the volumes of these tests would be sufficiently large (100 million tests in US alone each year) to assure profitability.
Diagnosis-related Group coding (DRG; where insurers pay a lump sum to hospitals for treatment) incentivizes hospitals to use inexpensive antibiotics, which places significant pricing pressure on new expensive antibiotics. But, it also incentivizes hospitals to get the initial antibiotic right since use of appropriate antibiotics early improves patient outcomes and reduces length of stay. i.e. hospitals get to keep more of the lump sum payment increasing their profit margins. In cases like Sepsis (which is one of the most expensive conditions to treat in hospitals), this makes a huge impact. It may even be the difference between whether the hospital is able to break even or not.
So, a well-designed diagnostic approach will garner strong stakeholder (patients, payers, society) support and command large volumes needed to be successful. It is difficult for antibiotics, with the healthcare and reimbursement models in effect today, to have such support or volumes.
Challenges
The one area where antibiotic development and diagnostics development share common ground is in investment attention – both struggle for it. Even well-intentioned programs like CARB-X and NIH grants do not devote sufficient funds for diagnostics development (see chart). While several governments, notably the UK, and the WHO have been campaigning for greater investment action, there are no moonshot initiatives to combat antimicrobial resistance. All this despite evidence that an appropriate diagnostic would allow us to dramatically improve the efficiency of existing drugs and buy us time to develop other long-term strategies.
Even though the market is huge, the impact is huge, and there is a real problem in need of a solution, limited resources (human and financial) have been devoted to this area and problem. So, we find ourselves in the situation today where there is no diagnostic that can help physicians determine if an antibiotic is necessary and which one to use. The core technology we use is effectively the same since the early 20th century!
This is partly because the approaches being attempted use the same basic strategy as those that have been tried before (that did not yield desired outcomes) with advances in technology incorporated. so, it is not too surprising that they have not yielded the desired results. The willingness to adopt a high-risk high reward strategy by investors as done in areas such as oncology therapeutics has been conspicuously absent. It’s not that investors are not aware of the challenges posed by AMR and Sepsis or the need for a solution. But, there needs to beat least one good commercial success story to renew the interest in this space. The high rewards are not readily apparent to investors burned by previous approaches. New, improved technical solutions and business models have not matured/been developed either. And this paucity of solutions is only made more difficult as talent seeks the security of better-funded areas.
They have been proposals to increase the economic incentives for developing much needed antibiotics. So far these well intentioned efforts have not resulted in some technical success but not the growth of self-sustaining companies. Pragmatically the success story is more likely to come via diagnostics (for the reasons outlined above) than in therapeutics. Or through a combination of diagnostic and therapeutic approaches enabling precision medicine for infectious diseases.
Progress
Despite these challenges, we are optimistic about the prospect of new innovative solutions and our platform, Biospectrix™. The ideal diagnostic should be able to detect the presence/absence of bacteria, determine its identity, and if it is antibiotic resistant – all in 15-60 minutes. Early results in our lab indicate that we can meet all of the above requirements.
With our approach, we aim to isolate, detect, and identify bacteria in < 1 hour without destroying the bacteria. The information from the analysis is utilized by the physician to administer the appropriate antibiotic. Through this process, patient outcomes will improve, length of stay in hospitals will decrease, hospital profit margins will improve, and, crucially, we can slow down the spread of antimicrobial resistance by cutting down on inappropriate antibiotic use. This is an outcome worth persevering for.
And, by the way, once we are done with our analysis, the bacteria can be cultured (from the sample we analyzed) and subjected to further analysis, if needed, but without the time pressure.
Enabling targeted therapy will permit new antibiotics being used judiciously as opposed to simply being saved as a method of last resort when it might be too late. Judicious use would provide the volumes needed for antibiotic developers to be profitable. It would also prolong the life of existing drugs. The possibilities for individual and societal good and commercial success are tantalizing. And that is why we believe that diagnostics are the place to start to combat AMR and Sepsis.
There is still some ways to go and many challenges to overcome before this vision becomes reality. But, we do so knowing that technical and commercial success with a positive impact on patients and healthcare, as we know it, is near. Jim O’Neil stated in his assessment on antimicrobial resistance, “One of the greatest worries about AMR is that modern health systems and treatments that rely heavily on antibiotics could be severely undermined.” We intend to do our part in preventing this bleak scenario from becoming reality.
