The Pharmaceutical Journal Vol 265 No 7113 p366-368
September 9, 2000 International

World Congress of Pharmacy

The impact of new science and technology on pharmacy practice

Advances in drug research in the new decade

Professor DOUWE BREIMER (Leiden/Amsterdam centre for drug research, Leiden university, the Netherlands) pointed out the importance of thinking globally. Indeed, drug development had proceeded on a global basis for a number of decades, and it was clear that this would continue. Pharmaceutical companies were not interested in developing drugs for use in one country, and medicines would be marketed world-wide more and more. This would make the FIP increasingly important. Growing emphasis was being placed on defining and meeting unmet needs in terms of disease management for individual patients. To meet these needs, there was a requirement not only for knowledge but also to translate that knowledge into technology, including new chemical entities (NCEs) and new drug delivery systems. The implications of the human genomic programme, including the possibility of new diagnostic capabilities, increased precision in therapy, genetic or gene-regulating medicine together with the need to counsel high-risk patients on lifestyle, were enormous. And because of an improved understanding of the molecular mechanisms of disease, there would be a paradigm shift from treatment of disease to prevention and cure.

Douwe Breimer: new training paradigm

Mechanisms of the future
The medicines of the future would be, as many were now, mechanism-based small molecules, but there would be several new classes of drugs and their mechanisms would be better understood. There would also be proteins and other macromolecules, gene-regulating agents (eg, oligonucleotides), and gene therapy, which would be used for specific purposes. The knowledge base underpinning new drugs would be much greater in the future than it was today, but to achieve this was no small matter, not least because of the cost.
Drug development had to become cheaper, and drug therapy had to be tailored to individual patient need. Current drug development was not sufficiently discriminatory between patients and between products, and there was a need to generate quality information on the safe and effective use of drugs in individual patients. This knowledge represented the "software" of pharmaceutical products, but because a myriad of factors, both genetic and environmental, influenced susceptibility to disease and response to drug therapy, developing this information represented a "major challenge".
What had increased recently was an appreciation of genetic factors involved in drug metabolism. For example, it had been learnt that cytochrome P450 had a number of isoforms, which had different substrates; 2D6 was one of these isoforms, and 6 to 10 per cent of the population were defective in it. Genetic polymorphisms affected a number of other P450 isoforms, as did other factors, such as age, enzyme induction and inhibition, disease, smoking, alcohol, grapefruit juice, nutrition, pollutants, concomitant medication, and so on. It was, therefore, important to know in advance which P450 isoform was involved in the metabolism of a newly developed drug and also of any polymorphisms.
Another hot topic on the research agenda was "drug transporters". Having an influence on bioavailability and drug distribution to target sites, these included amino acid and peptide transporters, nucleoside transporters and multi-drug resistance transporters. The old adage that drug transportation across the blood-brain barrier depended on lipophilicity had been overturned about 10 years ago with some drugs (eg, vinblastine, vincristine) not being transported across the barrier as predicted.
Such "revolutionary insights" were exciting and would continue to have an impact on drug development, but a number of drugs still failed in the developmental stage due to inadequate absorption, distribution and metabolism and a lack of clinical efficacy. So, there was clearly a need to do better. However, selection of new compounds was increasingly being based not only on pharmacokinetics, but also on pharmacodynamics and pathophysiology - factors which did not remain constant with time in one individual, but which needed to be taken into account to optimise drug therapy.
Biomarkers, such as blood glucose, blood pressure, skeletal muscle tension and EEG and ECG signals, could be used to monitor the severity of a disease on an ongoing basis and this information could be fed back to the drug delivery system to adjust the dose as necessary. Although this would probably not be feasible in the treatment of patients for the next 10 years, it could, and should, be used in drug research.

Challenges
The challenges for new drug science rested mainly in terms of bridging gaps - gaps between in vitro and in vivo experimentation, gaps between pre-clinical and clinical studies, gaps between pharmacology and therapeutics, and the overall population versus the individual patient. Bridges also had to be built at school of pharmacy level. Unless the "brick walls" between pharmaceutical chemistry, pharmacology and pharmaceutics were broken down, pharmacy schools would become extinct. What was needed was a new training paradigm with pharmaceutical science in the middle linked to biochemistry, cell biology and all the other disciplines. This was the only way to move pharmaceutical science forward, Professor Breimer concluded.

Opportunities in screening and monitoring

According to Professor ANDREW MORE (executive editor of Bandolier, Oxford, England), the philosophy of evidence-based medicine was one that could not be ignored either now or in the future. But there was also a need to understand how the fruits of evidence-based medicine could be used. The core of evidence-based medicine lay in the systematic review in which all the papers relating to a specific clinical question had to be identified. World-wide, there were 30,000 medical journals publishing a total of six million papers a week, but 90 per cent of these papers were scientifically flawed and should not be read. Systematic review or meta-analysis represented a method of distilling and integrating information and using quality filters to ensure that the information considered was the best. This "chunk of knowledge" which, if developed properly, would stand the test of time, then had to be applied to individual patients in different parts of the world with their different environments and different sets of values. A great deal had been learnt about research that had the potential to mislead. Thus, trials that were not randomised could lead to a 40 per cent overestimate of treatment effects, trials that were too small to a 30 per cent overestimate, and trials that were not double-blinded to a 17 per cent overestimate. No such trial methodology led to an underestimate of treatment effects. For example, double-blind trials had shown no benefit of acupuncture over sham acupuncture and homoeopathy over placebo, whereas non-blinded trials had demonstrated benefits of both these therapies. What was needed was "to avoid making the measurable important and find ways to make the important measurable". Unfortunately, systematic review or meta-analysis had the capacity to produce a lot of statistics that were difficult to understand. Probability (P) values were no longer good enough, but statistics such as odds ratios and relative risk were not widely understood. Simpler and more effective ways were needed to communicate knowledge that could be used to answer the practical question of "how to treat Mrs Jones". The "number needed to treat" (NNT) had represented a step in the right direction, but there was now a move to looking at the number of patients who had the desired outcome together with the 95 per cent confidence limits. When looking at the efficacy of treatment for migraine, what was really necessary was to find out the number of patients who were free of pain. It was also important to know what happened to those patients who were not free of pain - the non-responders. Patients who did not respond to treatment were expensive in terms of visits to doctors, consultants and outpatients departments.

Andrew More: looking forward

Rubbish
All these principles applied not only to assessing different therapies, but also to adverse drug reactions, diagnostics, and so on. Of the total world literature in diagnostics, 99.9 per cent was rubbish. To come to such conclusions using the principles of evidence-based medicine clearly involved looking back at the literature. But evidence-based medicine was not just about looking back but looking forward, too, simply because the knowledge generated from it provided information on how to do better studies in the future that would bring real benefits more rapidly, Professor More concluded.

Can we afford genomics?

Dr FRANÇOIS SCHUBERT (vice-president, global health outcomes, Glaxo Wellcome, Canada) explored the economics of genomics in drug therapy and discussed the potential impact on health care delivery and pharmacy practice. Application of genetic knowledge heralded a revolution in the prevention and treatment of disease, with more accurate prognoses, more targeted treatments and new mechanisms of treatment to explore. However, the impact of these developments on health care costs were complex and uncertain. The treatments themselves might be costly, but they might reduce the use of health care resources.

François Schubert: get the information infrastructure right

Impact The impact of genomics on health care resources would be influenced by a number of factors, including the effectiveness, number and costs of treatments employing genetic treatments, the speed of medical advance and the reaction of health care regulators, all of which were largely unknown at this stage.
The term "genetic testing" needed to be defined carefully and it comprised two strands - disease genetics, which involved testing for the genes causing or being associated with disease, and pharmacogenetics, which involved testing for the genes for drug metabolism and/or drug action and hence which drugs would produce a response. Benefits of genetic testing included new insights into disease and medicines, and the potential for optimal drug response. However, there were risks in terms of providing unsolicited information within a family and the associated legal, ethical and social implications.
In terms of disease genetics, the discovery of BRCA 1 and 2 (the genes associated with an increased risk of breast cancer) provided an option for surgery to minimise the risk of breast and ovarian cancer. Identification of the genes related to Alzheimer's disease - and there were three common alleles, APO4, 3 and 2 - provided opportunities for new treatments, while a total genetic scan could give an indication of, for example, the probability of coronary heart disease or risk of dementia. Such knowledge could help individuals to prepare for the future and consider treatment options to minimise risk.
The overall cost impact of disease genetics was difficult to measure. New screening procedures, counselling services and preventive strategies would increase costs, but the avoidance or delay of disease or a decrease in disease severity would lead to reductions in medication, fewer visits to doctors and shorter hospital stays and hence could lead to lower costs. But whether health care systems could cope was unknown. Health care budgeting tended to be short term, but the benefits of disease genetics would only be realised in the longer term. The options were to restrict access, introduce co-payments, or be more flexible in moving funds across the health care system.
In terms of pharmacogenetics, a link had been found between the response to treatment with pravastatin and polymorphism of the CETP gene. Patients with the CETP gene responded to the drug, whereas those without the gene did not. Clozapine was another example, and patients with certain alleles at the 5-HT2A receptor responded better to the drug than those without. Potential benefits of pharmacogenetics included reductions in adverse drug reactions and a lowering of the costs associated with drug-related morbidity and mortality. Treatment could be more effective because it was better targeted, and there could eventually be a reduction in unnecessary drug use and costs of diagnoses.
However, as was the case for disease genetics, the overall costs of pharmacogenetics were difficult to measure. While fewer adverse events, reductions in unnecessary drug use and improved outcomes could reduce costs, the advent of curative health care would increase demand and hence costs.

Issues
Again, pharmacogenetics raised several issues. What would happen to those who had a disease for which there was no treatment? This had implications for counselling. The advent of new therapies would reduce resources in some parts of the health care budget, but increase them in others, and money would have to be moved around with more flexibility than was currently the case. How rapidly would new technology be introduced into health care? Would all countries be able to afford it? And how would the increasing requirements for information be managed? Who would develop the infrastructure? Pharmacists had to address these issues, Dr Schubert said. This was because in the future pharmacists would be providing a medicine that effected a cure, not just one that managed symptoms. And if pharmacists did not grasp this opportunity, others would.
Indeed, genetic technology could lead to an increasing role for pharmacy, in that doctors would diagnose and pharmacists could select treatments on the basis of pharmacogenetics. But to enable this to happen, there was a need for appropriate education and getting the information infrastructure right, he concluded.