The term personalized medicine has been used for many years, I can certainly remember it being a buzz word when I started my research career at the start of the century, and it has been practiced in a limited form for over a hundred years. However, with recent advances in science and technological developments, we are on the cusp of personalized medicine becoming standard practice rather than used in certain circumstances and conditions. In this article I will briefly overview what personalized medicine is, the technology that makes it possible and what the future potentially holds.
What Is Personalized Medicine?
Traditionally a medicine has been produced to treat a specific disease or ailment and everyone with the ailment would receive the same treatment, however it would typically result in many different outcomes. The optimal result would be that everyone would benefit from the medicine, but in reality a good proportion would possibly benefit and the treatment delivers the expected outcome, but for some the medicine would have no effect and potentially for some it would have a negative effect of not treating the condition and producing unwelcome side effects. The reason for this is that everyone is different at a genetic and molecular level and as such it is incredibly difficult to design a medicine that produces the same effect across a group of slightly different people. The goal of personalized medicine is to gain a greater understanding of a person’s genotype and phenotype and match drugs that are more likely to deliver a positive outcome in those individuals. For example, person 1 receives drug x while person 2 gets drug y for the treatment of the same ailment.
The obvious benefits from this personalized medicine approach are that recipients are going to receive treatments that will work and not produce any unwelcome side effects, but also cost savings in the longer term as expensive medicines are only given to those that will benefit rather than to all.
There are already numerous examples where personalized medicine is beginning to be used; one of the first significant demonstrations was with the drug Imatinib (‘Gleevec’) which inhibits the BCR-ABL tyrosine kinase. Many suffering from chronic myleoid leukaemia (CML) contain the BCR-ABL gene and as such Gleevec offers a very targeted, and successful, treatment. The drug cetuximab (‘Erbitux’) has been shown to improve the survival rate of those suffering from colorectal cancer if they carry a mutated EPGF gene, but not a mutated KRAS gene. As our understanding of diseases and drug mechanisms increases, then personalized medicine becomes more feasible. The route to personalized medicine though requires knowledge on the underlying basis and causes of disease, diagnostic tests to be able to identify and monitor the disease causing elements as well as new and a wider array of drugs to target the newfound disease causing agents.
Technology Behind Personalized Medicine
Much of the early work and attention has been focused on understanding the genome as the source of potential differences in populations and targets for personalized medicine. DNA sequencing is used to sequence human genomes to identifying genetic causes of disease and then screen individuals to see if they have the gene(s) of interest. A targeted drug can then be offered or withheld depending on that person’s genetic makeup and whether they are likely to respond to that drug. As the time and cost to sequence a whole human genome continues to decrease, DNA sequencing is a powerful tool in personalized medicine.
A person’s genetic makeup however only gives part of the story as a gene does not always get transcribed or only transiently or in a modified form, hence the proteome (the body’s proteins) also need to be studied. I like to use this analogue for genomes and proteomes; a genome tells you what could happen, a proteome is what is happening now. Proteomics is intrinsically more difficult than genomics in that protein expression is transient, proteins exist in a broad dynamic range and each protein can exist in multiple different forms due to post-translational modifications. The technology of choice capable of handling this complexity, whilst also offering the required depth and speed of analysis is LC-MS (liquid chromatography - mass spectrometry). LC-MS offers similar benefits such as identifying drug targets, characterizing populations and individuals and diagnostics, but at a protein level.
A final, rapidly evolving, field is also driving personalized medicine and that is metabolomics. This investigates the cellular metabolites from biological processes to give a physiological snapshot of the cell. Mass spectrometry is again used for the identification and quantitation of the metabolites, but due to the diverse physio-chemical properties of the metabolites gas chromatography (GC), ion chromatography (IC) or liquid chromatography (LC) are used as separation technologies prior to mass spectrometry.
It is going to be the combination of genomic, proteomic and metabolomic data that is going to be required for accurate and personalized medicine. The technologies also need to offer speed, accuracy and sensitivity so that quick and accurate decisions are made for the individuals’ ongoing treatment.
Implications and Requirements of Personalized Medicine
Although progress is being made in personalized medicine there are still many hurdles to overcome and issues to still be resolved, including:
Technology – DNA sequencing and mass spectrometry are the two key technologies in personalized medicine and while both have undergone huge technological advances over the past two decades, there is still room for improvement. Increased speed at a lower cost per sample is a requirement as well as sensitivity and accuracy to allow for fast analysis of samples to direct treatment, preventing mistakes and making precision medicine affordable to the general population.
Identifying targets and drugs – a greater understanding of systems biology, underlying and molecular causes of disease and the corresponding diagnostic test are required. Coupled to this, there also needs to be the corresponding drug discovery to find the treatments for the newly identified targets.
Clinical trials – the traditional approach of conducting a trial with hundreds of people in a group doesn’t fit well with personalized medicine and is likely to mean trials of many smaller groups with frequent measurements and adjustments over time. More discussion on this topic can be found in this interesting Nature Comment.
Pharmaceutical industry – the drug discovery cost is not going to reduce and with the potential changes to clinical trials then the cost to bring a drug to market is likely to increase. The drug is then likely to be beneficial to a smaller cohort of the population who fit the correct profile than a one-size fits all approach. The outcome is larger up-front development costs with potentially a lower payback.
Healthcare costs – with precision medicine it is likely healthcare costs will reduce as the treatment will be targeted and effective leading to a faster resolution and improved outcomes. However, initial costs are higher due to the profiling required, but overall should lead to lower healthcare costs.
Precision medicine offers the potential to revolutionize healthcare and is already being employed in some conditions. As our understanding of genomics, proteomics and metabolomics increases it can only increase the rate of adoption of precision medicine. However, there are still issues to resolve and technologies and processes to be fine-tuned as we progress.