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Pipeline Potential

James Sawyer of Prism Ideas explains how far personalised medicine has comes, but stresses that the challenge now is identifying different subtypes of patients so that treatment can be truly tailored to the individual

Since ancient times, physicians have attempted to personalise treatments by considering indicators such as age, weight and medical history. The vast expansion in medical knowledge over recent years has meant that health indicators available today have become more specific and reliable.

The Personalised Medicine Coalition defines personalised medicine as “the application of genomic and molecular data to better target the delivery of healthcare, facilitate the discovery and clinical testing of new products, and help determine a person’s predisposition to a particular disease or condition” (1). The main aim of personalised medicine – also known as individualised treatment, targeted therapy, or stratified care – is to get the right drug to the right patient, at the right time. To achieve this goal, various strategies have been used, including pharmacogenetics/pharmacogenomics, therapeutic drug monitoring and evidence-based medicine.


An accurate diagnosis is essential to achieve the best possible treatment outcomes. Recently, there has been much progress in the development of diagnostic tests, which range from simple blood or urinary tests to sophisticated techniques, such as magnetic resonance imaging and tissue staining (for example, in situ hybridisation), through to individual gene mapping. Simple, reproducible diagnostics are essential for uptake into clinical practice, since they must be integrated into standard hospital procedures and primary care practice rather than requiring specialist resources. Increasingly, technological platforms are being developed for genetic profiling of patients, which has the potential to offer widespread clinical benefits.

The identification of biomarkers to allow for early diagnosis can make a huge difference to patients’ prognoses. In testicular cancer, human chorionic gonadotropin and alpha fetoprotein are usually elevated and are reliable indicators of this disease. For prostate cancer, screening serum levels of prostate-specific antigen (PSA) is currently the standard of care in many countries. Nonetheless, much research is currently being performed to supplement or even replace serum PSA with more specific and informative biomarkers, which could potentially be tested in urine. Other biomarkers are being evaluated for the diagnosis and monitoring of pancreatic, gastric, lung and ovarian cancer.

For cardiovascular diseases, cardiac troponin T (cTnT) is an established prognostic marker in patients with acute coronary syndromes, while N-terminal pro-B-type natriuretic peptide (NT-proBNP) is an indicator of acute heart failure. A retrospective study examining the additive prognostic value of cTnT and NT-proBNP showed that patients with one or two markers exhibited five-year cardiovascular mortalities of 40 and 60 per cent, respectively, compared with 10 per cent in patients with no markers (2). Monitoring these markers could therefore predict adverse outcomes and focus healthcare on those with greatest risk.

Genetic testing for breast cancer -1 and -2 gene (BCRA-1 and -2) mutations has identified women who are at a 75 per cent higher lifetime risk of breast cancer than those without these mutations. However, BRCA-positive patients account for only 10 per cent of all breast cancer cases. Furthermore, although 25 per cent of BCRA-positive patients will never develop breast cancer, many of these women have prophylactic mastectomy/oophorectomy. Other risk factors such as age, number of first-degree relatives with breast cancer, nulliparity and number of benign breast biopsies have been used to identify women at high risk of breast cancer. In such women, prophylactic treatment with tamoxifen for five years significantly reduces breast cancer risk over 10 years compared with placebo (risk ratio 0.73; p=0.004) (3).

Not all diagnostic tools need to be laboratory-based. The Migraine Disability Assessment Scale (MIDAS) is a five-item questionnaire evaluating the burden of illness. MIDAS has proven its validity as an accurate, cost-effective tool for the stratified care of patients with migraine, based on symptom severity (4). It allows those patients whose illness is most debilitating to be identified and begin treatment with a triptan early, rather than wait for common analgesics to fail.


Undoubtedly, oncology is the field in which personalised medicine has achieved the greatest use. Clinical developments have enabled the classification of patients into various subtypes, based on anatomical and pathological findings. Nowadays, samples from cancer patients are routinely tested for relevant biomarkers in order to tailor the treatment (see Table 1).

In breast cancer, genetic testing (for example, using Oncotype DX® or MammaPrintTM) is becoming common practice to establish each patient’s risk of recurrence and oestrogen receptor (ER) status (5,6). Testing for ER positivity enables physicians to determine the likelihood of response to endocrine therapy and provides a variety of treatment options. Another important marker in breast cancer is the human epidermal growth factor receptor (EGFR) 2 (HER2), which is present in around 25 per cent of cases and is associated with an aggressive form of the disease. The monoclonal antibody trastuzumab targets HER2 and is only active in patients expressing this receptor.

Similarly, EGFR is a relevant biomarker in several tumour types, including breast, lung and colorectal cancer. EGFR inhibitors currently licensed to treat advanced nonsmall cell lung cancer include gefitinib and erlotinib. However, unlike HER2, amplification of EGFR alone does not correlate with response to treatment; instead, drug susceptibility is determined by the presence of EGFR mutations, which make patients responsive to these inhibitors. Since progression-free survival with gefitinib over chemotherapy is significantly longer in patients bearing EGFR mutations (7), it is now recommended that lung cancer patients are stratified according to their EGFR status prior to treatment.

Another important biomarker is KRAS, the product of the oncogene K-ras, which encodes a GTPase involved in multiple intracellular signalling pathways. The presence of a mutated version of KRAS is associated with the development of several malignancies, including pancreatic and colorectal cancer. In the latter, patients bearing mutated K-ras do not benefit from treatment with the monoclonal antibodies cetuximab or panitumumab, so KRAS acts as a marker to exclude certain therapies (8,9).

In patients with hormone-refractory prostate cancer, an innovative, truly personalised treatment has recently been developed. An autologous cellular immunological agent (Sipuleucel-T) is combined with the patient’s own tumour antigens and antigen presenting cells (APCs), and cultured ex vivo in the presence of prostatic acid phosphatase and granulocyte-macrophage colony-stimulating factor. This leads to the activation of the APCs, which are infused back into the patient’s blood stream to specifically target the tumour.


Personalised medicine can also identify those patients more likely to experience adverse reactions to a drug. Thus, in breast cancer patients, cytochrome P450 2D6 (CYP2D6) gene variants associated with impaired tamoxifen metabolism are linked to increased toxicity associated with tamoxifen treatment. Therefore, testing for CYP2D6 variants helps assess a patient’s suitability for tamoxifen treatment and allows alternative treatments to be considered.

In cardiovascular disease, patients carrying cytochrome P450 CYP2C9*2 or CYP2C9*3 alleles are at a significantly increased risk of bleeding (at a hazard ratio of 2.39) during warfarin treatment, compared with those who carry wild type CYP2C9 (10). Although using CYP2C9 allele information to adjust the warfarin dose has been shown to improve efficacy and safety in these patients, routine CYP2C9 genotyping is not advised in clinical practice and is not intended to replace the international normalised ratio (INR) blood coagulation test, which is an effective monitoring tool for patients receiving anticoagulant therapy (11). Current algorithms for warfarin dosing take both INR values and genotype information into account (when available) to calculate the most appropriate warfarin dose for individual patients.

Genetic testing for increased susceptibility to adverse drug reactions (ADRs) is also being performed across indications such as colon cancer, HIV infections, leukaemia, epilepsy and psychiatric disorders such as bipolar disorder and schizophrenia.


As our understanding of the biology of disease increases, illnesses are divided into more and more subtypes and it is essential that only patients with the relevant characteristics/biomarkers are treated. This achieves the best possible efficacy and minimises toxicity by not treating patients who would not respond to a particular drug or are likely to experience ADRs. While personalised medicine guides the development of new drugs for specific patient populations, the need to identify patient groups drives the requirement for companion diagnostics. For example, as HER2 is only expressed in around 25 per cent of patients with breast cancer, if trastuzumab had been tested in unselected patients its efficacy would have been missed. The ability to reliably identify HER2-positive patients allowed the benefit of trastuzumab to be demonstrated.

While data from the human genome project has identified genes that may be linked with certain diseases, work on proteomics (that is analysis of the proteins encoded by genes) is also important. In fact, many of the currently available cancer tests are protein- rather than DNA-based. Recently, an antibody panel using six different antigens has been clinically validated for lung cancer diagnosis, and it is hoped that it will identify high-risk patients requiring more aggressive treatment (12).

Multi-factorial illnesses, such as psychiatric disorders, pose additional challenges because of their complex aetiology: hundreds of different genes and environmental factors are potentially involved. For instance, nearly one fifth of patients with schizophrenia are defective in CYP2D6 enzymes, which metabolise approximately 40 per cent of antipsychotic drugs, thereby influencing their efficacy and safety (13). Therefore, pharmacogenetic testing prior to selecting treatments may prove useful.

Another example of a progressive illness with high morbidity is rheumatoid arthritis, where around 30 to 40 per cent of patients do not respond to treatment with anti-tumour necrosis factor agents. While better identification and stratification of potentially responsive patients will optimise resources, new therapies are still needed for unresponsive patients. Improved diagnostic criteria and better prognostic markers are also required to identify patients with poorer prognoses, so that treatment can be initiated early and joint damage prevented. Currently, the lack of specific biomarkers to predict the course of the disease precludes targeted therapy being properly applied to improve remission rates (14).

Overall, the validity of a personalised approach to clinical practice has been demonstrated in randomised controlled trials (RCTs) across many therapy areas. For example, several large RCTs confirmed the efficacy of tamoxifen in patients with ER-positive (but not ER-negative) early breast cancer. In lung cancer, the efficacy of EGFR inhibitors, such as gefitinib, has been examined in selected versus unselected populations (7). In migraines, the predictive validity and usefulness of the MIDAS tool in stratified versus stepped care was demonstrated in the Disability in Strategies of Care trial (4). The difficulty now is more about identifying subtypes of patients across each major disease so that treatment can be truly tailored to the individual patient.


Personalised medicine facilitates identification of costeffective therapies, which is critical in light of the continual pressure on healthcare spending. However, the impact of personalised medicine on health policy is complex and needs to be addressed at various levels, from general practitioners to hospital consultants, to treatment guidelines and government health policy makers. Country-specific requirements and regulations will also have to be considered. Another important issue that must be addressed is that of private health insurance; if genetic testing is routinely incorporated as a screening tool, patients who test positive for potential cancer markers may see their insurance premiums rise.


The enduring success of personalised medicine relies on our ability to match our growing understanding of disease biology with the identification of new molecular targets and suitable therapies. These therapies need to be accompanied by tools to select the relevant patient subgroup, ultimately leading to their effective application in the clinic. These tools need to be reliable and effective, and also easily accepted by the patients and their treating clinicians. Ultimately, this approach should yield treatment strategies with greater effectiveness and lower toxicities, which are also costeffective in the long term.

In the case of future assays and diagnostics, these will need to be incorporated into simple algorithms that stratify patients into appropriate care groups. Therefore, there is a need to design and deliver more strategy-of-care studies to demonstrate that the proposed tests facilitate the decision-making process and ultimately improve patient outcomes.

While there have been resounding successes in the implementation of personalised medicine, providing care for future patients also necessitates the development of novel healthcare delivery models, together with new approaches to clinical trial design, assessment of therapeutic value, and clear guidance on the approval and reimbursement of emerging treatments.

  1. Abrahams E, Ginsburg GS and Silver M, The personalised medicine coalition: goals and strategies, Am J Pharmacogenomics 5: pp345-355, 2005
  2. Zografos GC and Roukos DH, Innovative biomarker development for personalised medicine in breast cancer care, Biomark Med 5: pp73-78, 2011
  3. Cuzick J, Forbes JF, Sestak I, Cawthorn S, Hamed H, Holli K and Howell A, Long-term results of tamoxifen prophylaxis for breast cancer; 96-month follow-up of the randomised IBIS-I trial, J Natl Cancer Inst 99: pp272-282, 2007
  4. Lipton RB, Stewart WF, Stone AM, Lainez MJ and Sawyer JP, Stratified care versus step care strategies for migraine: the Disability in Strategies of Care (DISC) Study: A randomised trial, JAMA 284: pp2,599-2,605, 2000
  5. Zujewski JA and Kamin L, Trial assessing individualised options for treatment for breast cancer: the TAILORx trial, Future Oncol 4: pp603-610, 2008
  6. Cardoso F, Van’t VL, Rutgers E, Loi S, Mook S and Piccart-Gebhart MJ, Clinical application of the 70-gene profile: the MINDACT trial, J Clin Oncol 26: pp729-735, 2008
  7. Mok TS, Zhou Q, Leung L and Loong HH, Personalised medicine for non-small-cell lung cancer, Expert Rev Anticancer Ther 10: pp1,601-1,611, 2010
  8. Karapetis CS, Khambata-Ford S, Jonker DJ, O’Callaghan CJ, Tu D, Tebbutt NC, Simes RJ, Chalchal H, Shapiro JD, Robitaille S, Price TJ, Shepherd L, Au HJ, Langer C, Moore MJ and Zalcberg JR, K-ras mutations and benefit from cetuximab in advanced colorectal cancer, N Engl J Med 359: pp1,757-1,765, 2008
  9. Amado RG, Wolf M, Peeters M, Van CE, Siena S, Freeman DJ, Juan T, Sikorski R, Suggs S, Radinsky R, Patterson SD and Chang DD, Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer, J Clin Oncol 26: pp1,626-1,634, 2008
  10. Higashi MK, Veenstra DL, Kondo LM, Wittkowsky AK, Srinouanprachanh SL, Farin FM and Rettie AE, Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy, JAMA 287: pp1,690-1,698, 2002
  11. Caraco Y, Blotnick S and Muszkat M, CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomised controlled study, Clin Pharmacol Ther 83: pp460-470, 2008
  12. Boyle P, Chapman CJ, Holdenrieder S, Murray A, Robertson C, Wood WC, Maddison P, Healey G, Fairley GH, Barnes AC and Robertson JF, Clinical validation of an autoantibody test for lung cancer, Ann Oncol 22: pp383-389, 2011
  13. Cacabelos R, Hashimoto R and Takeda M, Pharmacogenomics of antipsychotics efficacy for schizophrenia, Psychiatry Clin Neurosci 65: pp3-19, 2011
  14. Bykerk V, Unmet needs in rheumatoid arthritis, J Rheumatol Suppl 82: pp42-46, 2009

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James Sawyer is the Chief Executive Officer of Prism Ideas. Following a clinical career in general medicine and anaesthetics, James moved to the pharmaceutical industry in 1993, holding leadership positions in companies including Sanofi-aventis, AstraZeneca and Roche. James’s clinical development experience spans all phases of clinical research and he has published widely across a variety of therapeutic areas. He has driven regulatory interactions for many compounds and is the author of several expert reports filed at European and North American Agencies. James founded Prism Ideas in 2001. Email:
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