It is a commonly encountered view from the quantitative bioanalysis community that high resolution mass spectrometry (HRMS) is a qualitative technique employed by biotransformation chemists working in “the other” mass spectrometry laboratory. The “high res” laboratory often operates outside of the well-defined bioanalytical method validation guidelines to analyse R&D output or probe the often complicated metabolic pathways of drug candidates to inform development strategies.
However, HRMS affords the bioanalytical scientist a number of advantages not available when using conventional tandem triple quadrupole (QQQ) platforms, namely significantly better selectivity and the ability to multiplex quantitative and qualitative workflows. This acquired data can be mined post processing to provide the researcher with a comprehensive view of analyte behavior and fate.
Conversely there are perceived disadvantages to the application of HRMS technology in the quantitative space with low sensitivity, a limited dynamic range and robustness concerns often cited as technical reasons for the slow uptake of HRMS. That said there have been significant efforts in the development of software and hardware solutions that, to a large extent, have closed the utility gap for HRMS in the quantitative space.
To this end the Bioanalysis journal produced a special issue focusing on HRMS in 2012 Volume 4(5). In the subsequent four years, the application of HRMS in the bioanalytical arena has unquestionably seen growth but perhaps not as much as some commentators predicted. It is in this landscape that the Bioanalysis Zone has conducted a Spotlight survey on “The Rise of Quantitative HRMS”, the results of which are discussed here.
Reflecting on the results of the survey it is interesting to note that a total of 80 responses represent a broad global geography with the highest number coming from Europe (44%) and the United States (37%). Of the survey respondents, most were employed in the Pharmaceutical Sector (31%), followed by Contract Research/Manufacturing Organisations (25%) and the Academic sector (14%). It is notable, however, that only 5% considered their laboratory to be in the Biotechnology Sector. One might consider this to be surprising as quantitative HRMS has a number of advantages in the biologics space but this potentially anomalous response may be explained by the large number of pharmaceutical companies involved in the development of biologic therapies in addition to the development of small molecule xenobiotics. The majority of responses (52%) came from individuals identifying themselves as Scientists as opposed to Managers (43%). Taken in the round this represents a broad cross section of the quantitative bioanalytical community.
Interrogating the survey results further it is interesting to note quantitative HRMS is currently employed across multiple classes of molecules. The majority of respondents work with peptides and small molecules (55% each) followed by therapeutic proteins (37%), endogenous compounds (36%) and therapeutic antibodies (30.7%). Perhaps surprisingly, only 13% of respondents indicated that quantitative HRMS is utilized in their laboratories for the analysis of oligonucleotides. It could be perceived that the high selectivity afforded by HRMS would pose a significant advantage when analyzing oligonucleotides and it is possible that the comparatively low indication is due to the weight of laboratories working with xenobiotics and proteins rather than oligonucleotides.
Nevertheless, it is clear that HRMS demonstrates a broad utility in today’s quantitative laboratories. This is further illustrated by the data comparing the volume of qualitative vs quantitative endpoints supported in the surveyed laboratories. The survey data suggests the cohort applying HRMS to 50% of their quantitative work mix is larger than the cohort utilizing HRMS exclusively for qualitative endpoints.
Given the seemingly broad application of HRMS to quantitative endpoints it is of interest to understand what is driving the uptake: is it the specific advantages of HRMS instruments or are the perceived limitations of QQQ analyses forcing bioanalysts to investigate new or different techniques for quantitative analysis? To shed some light on these factors the survey sought to probe the characteristics or limitations displayed by QQQ platforms in the quantitative space. On a scale of 1–5 respondents highlighted that the biggest limitations of QQQ analyses were sensitivity (4.39/5), followed by ruggedness/reliability (4.28/5). Throughput (4.15/5), selectivity (4.12/5) and cost (4.06/5) made up the remainder of the described limits. This data set is most interesting as the main limitations associated with QQQ are some of the main perceived limitations with HRMS platforms. To this end, it must be surmised that it is not the limitations of QQQ instruments that are fueling the interest in HRMS but instead the unique advantages afforded by HRMS over QQQ.
The main benefits and advantages of HRMS were recognized by survey respondents as being enhanced specificity with respect to QQQ platforms and the unique ability to mine full scan data. It would be a sensible interpretation of the survey data to suggest that the unique capability of interrogating acquired full scan data is driving the significant uptake of HRMS in the R&D space: 64% of respondents indicated HRMS is applied in R&D compared with only 20% for regulated bioanalysis. The survey then goes on to question the audience about the barriers to entry for quantitative HRMS, particularly in the regulated space.
Respondents expressed the greatest concerns about a perceived lack of sensitivity and the cost of HRMS platform. One might presume that as the technology further matures, sensitivity gains may be routinely afforded and the overall cost of ownership would decrease. It can therefore be assumed from the survey results that a number of laboratories have adopted a watch-and-wait policy prior to significant investment. Other technical concerns less frequently highlighted included instrument software and limitations of laboratory staff’s technical understanding. Interestingly, however, when the same question of HRMS limitations is framed within the context of regulated bioanalysis, user knowledge and experience was highlighted as the biggest barrier, followed by a lack of applicable guidance from the regulatory agencies. The indication of knowledge and experience gap is perhaps not too much of a surprise when one considers that the quantitative landscape is heavily invested in fleets of “gold-standard” QQQ platforms. It is, however, the concept of appropriate regulatory guidance that may prove to be the most significant barrier of all and one which is likely to influence the industry dialogue in years to come as companies seek to rationalize the number of different platforms used in their laboratories. The current quantitative paradigm with QQQ mass spectrometry is a discreet exercise with targeted transition(s), defined integrated peak(s) and easily applied acceptance criteria. The incurred data is easily understood and is simply stored and reconstructed. With quantitative HRMS analysis it is not arbitrarily simple to define what needs to be captured for reconstitution of results owing to the nature of the post-acquisition steps that can be applied. Moreover, where value-added full scan data is acquired in parallel with primary quantitative data consideration should be given to how the data is interrogated, documented and reviewed in order to maintain regulatory integrity.
Regardless of real or perceived barriers to routine adoption in the quantitative space, the survey respondents believe that the application of HRMS will increase. The number of individuals responding to the survey who currently use HRMS in 50% of their quantitative work still remains low at a figure of 10%. When asked to predict their work mix in 2020, 48% believe that HRMS will be applied as often as QQQ. Clearly this indicates that in this age of biologic promise, quantitative HRMS will continue to generate more interest within the bioanalytical community as the perceived hurdles to routine adoption are overcome. It will be interesting to observe whether future development of the technology will see this prediction realized.
ABOUT THE AUTHOR
Iain Love has worked in the Bioanalysis industry for 12 years and has been with Charles River for 2 years. Iain’s expertise lies principally in assay development in support of preclinical and preclinical analyses. In his roles at Charles River, Iain oversees the Development and Discovery Bioanalysis team. Iain’s team are routinely involved in the application of novel chemical and biological techniques in support of Discovery and Development programmes for a broad portfolio of chemical and biological drug candidates.