Cutting edge medical research

Where does ordinary Research end and Cutting-edge research begin? Research is defined as “a detailed and careful study of something to find out more information about it”. Thus, all research should be about exploring the boundary between the known and the unknown. Ideally, all research should be “Cutting Edge” (Fig. 1).

Fig. 1.

The rim of research. Cutting edge represents the outer margin of this rim.

Cutting edge research usually addresses important problems using latest technologies with a promise of high impact. Being involved in cutting-edge research translates to pushing the envelope of human knowledge and enables one to make significant contributions to one's field.

But much of the research, especially in colleges and during thesis work, does take place a little bit away from the edge, closer to the inner rim. This article will attempt to explore as to how one can identify the edge of research.

Steps to do “Cutting edge research”

A reasonably easy way is to follow the top journals in a given field to keep abreast of the latest research. Replicating the same in India still keeps one reasonably close to the cutting edge. While this is possibly one of the most popular approaches (and there is nothing inherently wrong with this strategy), there is definitely a certain charm in identifying research questions that emanate from one's own intellectual efforts.

There is no sure shot recipe to doing cutting-edge research. The suggested 4 step approach may be seen as one of the many possible approaches:

1. Choosing the space (Basic Vs applied research): Almost all research can fit into one of the two types, namely Basic or Applied research (Table 1).¹ While Basic Research is primarily driven by curiosity with no specific timetable or specific goals for new applications, it helps build a conceptual framework for better applications in the future. An example might be the desire to map the entire human proteome (as done by our group) using a set of 30 tissues.² A priori, it would be difficult to state the usefulness of such a research. However, such a research creates the fertile soil for further research which might find application in an unexpected field at some later point in time. Applied Research, on the other hand, aims to solve a real world problem in a better or faster or more economical way than achieved by the current methods. Findings from basic research helps to solve problems in novel ways while applied research often provides new insights that needs further exploration by basic research. In applied research, one might choose to work on various domains (Table 2) like:

Table 1.

Basic vs applied research.

S. No.	Domian	Problem statement	Existing technology	Guiding principle	Novel/apparent solution	Disciplines/Tools that combine	References
Applied research
1	Aetiopathogenesis	Can we discover biomarkers in Osteoarthritis?	No blood biomarkers currently	Novel proteins may be present in extremely low concentration and hence undetected as yet. Potential biomarkers.	Use a mass spectrometry based approach to identify novel proteins that are increased in synovial fluid, some of which are potential biomarkers.	Rheumatology, Proteomics, Bioinformatics, Systems biology	Balakrishnan L. Clin Poteomics. 2014
2	Diagnostics	Can cancer margins be determined in real time while surgery is on?	Frozen section, but the time to diagnosis is almost 30 min	Normal cells and cancer cells have different metabolic signatures	A surgical knife that combines electrosurgical dissection with rapid ionisation mass spectrometry to assess intraoperative tumour margins and signatures from biopsies in near real time.	Oncology, Mass spectrometry, metabolomics, Bioinformatics, Sensor technology	Angel PM. Clin Chem 2021
3	Therapeutics	Can we develop new drugs against specific cell receptors more rapidly than currently?	Animal testing followed by human trials	In silico drug discovery and testing	Drugs can be repurposed or new molecules tested in a cost effective and rapid way “In silico” with new technologies	Computational engineering, drug design, molecular docking, Simulation, Machine learning, Molecular biology, nanotechnology	Brogie S. Front in Che, 2020
		Most appropriate strategy in initiating ART regime for HIV patients in India	Empirical therapy with 3 drugs	Should drug resistance testing be done denovo in all patients	Compare two strategies using a Markov simulation model approach through two cohorts	HIV Medicine, Health economics, Markov models, Monte Carlo simulation, Simulation	Shankar S. MJAFI 2020
4	Prognosis & Predictions	Can Sepsis be predicted earlier in ICU enabling early treatment and rapidly than currently?	Multiple scores like APACHE2, SOFA etc	Machine learning and AI may discern hidden patterns giving early prediction	Prognosis can be predicted earlier by creating different machine learning models handling multiple variables.	Critical care, Machine learning, digital biomarkers	Moor M. Front Med 2021
		Can we predict the COVID -19 epidemic and assess the impact?	Extrapolate the data	Mathematical modeling using differential equations	Prediction was made combining available epidemiological data with CoVID dynamics and mathematical modeling	COVID dynamics, Epidemiology, Mathematical modelling, Differential equations	Chatterjee K. MJAFI 2020
5	Reach	How effective is Covishield vaccine in India?	In early 2021, needed to be ascertained	Modeling based on large dataset	Collect large data and analyse. VIN-WIN cohort collected data on 1.6 million population	Epidemiology, Differential equations, Mathematical modeling	Ghosh S. MJAFI 2021
Basic research
6	Curiosity driven	Can we map the entire human proteome?	None	Systematically catalog Proteins	Using a Mass Spectrometry based approach, the entire human proteome was mapped	Molecular biology, Proteomics, Systems Biology, Bioinformatics	Kim M. Nature. 2014

Table 2.

The process of identifying solutions using cutting edge research.

S. No.	Characteristics	Basic Research	Applied Research
1	Underlying principle	Curiosity driven. Seek to understand ‘What’, ‘Why’, ‘How’, ‘When’, ‘Where’, ‘Who” questions of various processes.	Solution driven. Seeks practical solutions for existing problems
2	Examples	Human genome project. Human proteome project	Comparing drug A vs drug B for disease X
3	Benefits	Increases basic understanding Engine for scientific advancement Foundation for applied research	Solves existing problems Provides nidus for basic research
4	Scope	Universal Benefits become apparent years to decades later at times	Local Benefits apparent immediately

(a)Aetiopathogenesis: These pertain to the “How” and “Why” questions of the illness.³ One might choose to address the host of diseases whose aetiology is still labelled as “Idiopathic” which is an opportunity staring at us.

(b)Diagnostic aspects: Exploring better diagnostic methods which are easier, more accurate or diagnose the illness at an earlier point in time. An example is that of “I knife” that can diagnose the edges of breast cancer in real time using the principles of mass spectrometry.⁴

(c)Therapeutics: Developing new drugs or comparing new drugs with gold standards with a hope of identifying an alternative that is more effective/has lesser adverse effects or is cost effective.⁵ In certain conditions (e.g. Rheumatoid arthritis or HIV) where the therapeutic armamentarium is ever expanding; exploring the optimal therapeutic strategy.⁶

(d)Prognosis and predictions: This can vary widely from prognosticating outcomes in Sepsis to predicting the course of COVID pandemic.^7,8

(e)Reach: Ideally, all medical advancements should be available to and accessible by everyone. This is often a big challenge due to logistics or cost, thus opening up opportunities for research in this area.⁹

2.Identifying problems: Identifying the problem to work on is probably the biggest challenge of all, and the most difficult aspect of doing research. Considering that all research takes time (whether “Good” or “Bad”, whether “Cutting edge” or not), it is a good idea to spend some time in addressing this aspect first. It is suggested that one reads a few journals regularly. This not only lets us know the current status of research in a given field, but saves us from reinventing the wheel.

It is also rather obvious that one must play to one's strength and competency. Problems are best identified from the area that one is working in. A Gastroenterologist is best suited to choose their problem related to Gut/liver, enabling them to exploit their expertise.

Problems are usually staring us in the face once we start looking. They are best visualised as “Gaps”. The gap between “where one would like to be” vs “where one is currently” with respect to the problem. We feel it in our gut (or emotions) first. Things that make us annoyed or angry or uneasy or helpless are exactly the problems waiting to be solved. For e.g. when faced with a poor patient (earning Rs 5000 a month) of spondyloarthropathy, where NSAIDs have failed and guidelines recommend Biologics that cost a few lakhs annually, we are clearly helpless. It is also an opportunity to explore alternate strategies.¹⁰

3.Home on to a topic: Let's say we are working on leprosy in India and are worried about the resistance in multibacillary leprosy. WHO recommends a 1 year treatment which many of us and our colleagues do not agree with, seeing the resurgence on stopping treatment.¹¹ We would like to look at the viability of bacilli on repeat skin biopsy. The current method of Morphological index has poor accuracy. We would like to explore a better way to assess viable bacilli by exploring certain functional characteristics of the bacilli. Since it is only the live bacilli that can express their genes and produce proteins, we can design studies utilising transcriptomic and proteomic analysis of the tissue sample.^{12, 13}

4.Exploring the edge: Once we have identified the problem, the search for a cutting-edge solution can be done keeping three principles in mind (Table 3):

Table 3.

Three key ideas to doing “Cutting edge research”.

S. No.	Idea	Explanation	Analogy	Example from Healthcare
1	Explore adjacent possible	The word ‘Adjacent Possible’ was coined by Dr Stuart Kauffman in his work on biological evolution. It represents all the elements outside but near the system. These elements represent opportunities for the system to form new connections and grow into.	All the friends of my friends (whom I don't know yet) are in the realm of adjacent possible. They are just one step away from becoming my friends too, should I take the initiative.	Diagnosing Pneumonia by listening to sound of cough using an Artificial intelligence (AI) based sound analytic app in a cell phone has been found to have high diagnostic accuracy.
2	Combine concepts	Combine concepts from across disciplines. Sometimes answers exist in other disciplines that we just have to borrow	There were over 1500 car manufacturers before Henry Ford. It was a small scale industry then and most manufacturers produced designer cars. Henry Ford combined car manufacturing expertise with production line technology (already in vogue in Beef industry) enabling Mass production of cars. The rest is history.	The above idea combines the principles of different sounds in different respiratory illnesses (auscultation) taught in medical school, to the idea of letting AI and mathematical algorithm analyse it better. By capturing it through a cell phone, it enables diagnosis over any distance.
3	Collaboration	There is a need to collaborate with experts of other domains once we have identified the entities that need to combine	The ubiquitous CT scan, with which we are all familiar with, represents a brilliant collaboration between Godfrey Hounsfield (Biomedical Engineer), Dr James Ambrose and Dr Louise Kreel (Radiologists) whose theoretical underpinnings were developed by the Physicist, Allan McLeod Cormack, who shared the Nobel Prize with Hounsfield.	Clinicians and Software experts (with expertise in AI) need to collaborate to bring the above idea to fruition.

(a)The adjacent possible: Coined by Kauffman in his work on biological evolution, ‘Adjacent Possible’ represents all the elements outside but near the system.¹⁴ These elements represent opportunities for the system to form new connections and grow into (Fig. 2). In the leprosy example above, it would represent exploring molecular techniques (gene expression, proteomics, metabolomics etc) to check viability.¹² Alternatively, one is aware of the differences in auscultatory findings between different types of respiratory illness. Taking the idea a step forward, one can try to diagnose various respiratory illnesses (e.g. Asthma Vs Pneumonia) by analysing the nature of cough itself.¹⁵

Fig. 2.

Adjacent possible explained. ‘A’ is connected to ‘1’ and thus ‘2’ (that is connected to ‘1’ but not to ‘A’) forms the adjacent possible (shown by dotted line). If A connects to 2, all the ‘3’ comes into the realm of Adjacent possible. The edge of the possible thus gets redefined.

(b)Combine: One needs to combine ideas across disciplines. Here the expertise of a dermatologist combines with that of a molecular biologist to evaluate a new diagnostic approach and design an appropriate study.¹³ In the pneumonia example, one can use combine the expertise of machine learning and Artificial intelligence in arriving at a diagnosis by differentiating between the sounds of various types of coughs into a cell phone using an app.¹⁶

(c)Collaborate: Once we know the domains that need to combine, we need to search out the collaborators. Most clinical research is transdisciplinary and involves collaborations with molecular biologists, epidemiologists, mathematicians and a host of other clinical specialists. The more diverse the team, the better it is as everyone brings a different set of expertise to solve the problem. The positive externality of this approach is that one can then have multiple brainstorming sessions with the collaborators on many other topics/challenges, encouraging cross pollination of ideas that enables us to discover novel ways of tackling problems.

Keeping an idea book (in print or electronic form) and jotting down various ideas is a good strategy and one must visit this book every week or so.

A word of caution

A couple of points need mention at this point.

(a) Access to very expensive and cutting-edge tools does not translate to cutting edge research if one is trying to answer a mundane question. It is not uncommon to see this phenomenon when an institution procures a new equipment worth crores and one suddenly finds access to this new toy. Limited by absence of a new idea, one resorts to using the new tool to reinvent the wheel.

(b) Cutting edge research and recognition/fame do not necessarily have a strong correlation.

(c) It is more difficult to get funding for curiosity-driven basic fundamental research than for some applied research.

Conclusion

It is more important to identify a good problem to solve than getting fixated on cutting edge research. Not all cutting edge research needs expensive tools. More often than not, the ‘cutting edge’ is in the idea that is being explored. Once we home on a good topic, one can search for a reasonably good approach using the principles of adjacent possible, combination with other disciplines and collaborating with them.