Drug development has evolved with many healthcare companies now using genetics informed drug development to create targeted and personalised therapies allowing clinicians to treat the underlying causes of a disease. Technological and data analytics advances have enabled researchers to expedite the process of mining drug development leads from vast amounts of genetic data. Genealogy companies are increasingly engaged in partnerships with universities, non-profit organisations and private healthcare companies, indicating the growing importance of genetic data to these companies. Researchers have used insights from genetic data to develop a better understanding of the mechanisms of human disease. However, it remains to be seen if the outputs from these partnerships will result in new therapies being brought to market.

Benefits of Combined Expertise

With the cost of drug development rising and healthcare companies operating in an increasingly competitive market, many are finding innovative methods of drug discovery. For many years, genealogy companies have been collecting genetic data and providing consumers with insights about their biological inheritance. Consumers typically receive information about superficial genetic traits, such as whether your hair is likely to lighten with sun exposure to more serious health related information such as the presence of a genetic mutation associated with disease. Genealogy companies have worked with regulators for permission to disclose information to consumers relating to a limited number of diseases, however strict limits remain on the information they can share due to the complex relationship between the presence of a genetic mutation and the likelihood of developing a disease (1).

Genetic data is highly valuable to researchers using techniques such as genome wide association studies (GWAS) to associate small differences in DNA sequences, called single nucleotide polymorphisms (SNPs), with diseases to find potential drug targets (2). Several genealogy companies in realising the value of large collections of genetic data have developed partnerships with universities, non-profit organisations and pharmaceutical companies to perform GWAS and other studies. For example, just one of the many well-known genealogy companies has lucrative collaborations, which enables multiple healthcare companies to access data from 80% of their over 5 million consumers who have consented to participating in research (3).

Investing in Data 

The average consumer who consents to sharing their data contributes to over 230 studies run by universities, non-profit organisations and healthcare companies (4). Through these collaborative studies researchers are seeking to better understand the genetic basis of a range of diseases including asthma, psychiatric disorders, cancers and Parkinson’s Disease to uncover new drug targets. A recent study has shown that therapies targeting a specific genetic mutation are twice as likely to receive regulatory approval, which is one of the stepping stones required to commercialise new therapies (5). While these collaborative efforts to interrogate vast genetic data sets are yet to result in the discovery of a new therapy, some would say it is only a matter of time before products discovered in this way reach the market.

CRC’s experienced Medical Affairs team has the expertise to understand and utilise insights from genetic data analysis for the purpose of demonstrating therapy value and supporting Medical Affairs related projects.

Reference:

1. Hayden, E. The rise and fall and rise again of 23andMe. 2017. Nature. Available at: https://go.nature.com/2wZ1RdE
2. A better way to find drug targets. 2017. The European Bioinformatics Institute. Available at: https://bit.ly/2GLnHco
3. Molteni, M. 23andme’s pharma deals have been the plan all along. 2018. Wired. Available at: https://bit.ly/2MFYcJF
4. Brodwin, E. DNA-testing companies like 23andMe sell your genetic data to drugmakers and other Silicon Valley startups. 2018. Business Insider. Available at: https://bit.ly/2NbVtsz
5. Ma, Y. Targeted drugs score more wins. 2019. Pharma in focus. Available at: https://bit.ly/2BA70xh

Medical affairs teams have a growing and important role in ensuring pharmaceutical and medical device companies successfully implement strategies to capitalise on digital technologies, advances in big data analytics and the ‘Internet of Medical Things’. Healthcare companies can now access and analyse vast amounts of healthcare data via sources such as wearable medical devices, electronic medical records and healthcare apps. Medical affairs teams equipped with the expertise to access, define, gather and interpret this data can generate valuable insights, thus providing unprecedented opportunities to improve patient outcomes.

Collaborating with Technology Experts

Many big pharma companies realising the growing importance of digital technologies have partnered with or even acquired health technology companies to capitalise on readily available expertise in data collection and analytics. One report listed 56 acquisitions and mergers in the digital healthcare space in 2018 alone, 13 of which had a combined value of $7.6 billion USD (2). One example is the acquisition by a pharmaceutical company of Flatiron Health, a company specialising in oncology specific electronic health record (EHR) software. Through this partnership the pharma company can utilise the technology and data analytics infrastructure needed to generate real-world evidence and in turn accelerate the development of, and access to, new cancer therapies (3).

Medical affairs is typically the function that takes the lead in interpreting data and generating evidence detailing product value for development of strategic communications activities tailored to various stakeholders. Achieving this in the digital age increasingly requires collaborations with data providers and analytics companies to integrate new ways of engaging with patients, monitoring their progress during clinical trials and collecting real-world data at lower cost (1). An example of one such collaboration between a pharmaceutical company and technology giant Apple involved use of the ‘ResearchKit’ app to monitor patients’ progress during a large rheumatoid arthritis trial. Incorporating use of the app enabled the pharma company to gather data on joint pain and fatigue using a mix of surveys and sensor-enabled tests (1).

Communicate Data Insights to Stakeholders

The deluge of health data can present a challenge for stakeholders including healthcare professionals (HCPs) and patients as they seek to understand the value of increasingly complex diagnostic and treatment options. Medical affairs teams with deep product and disease area knowledge and established relationships with key stakeholders are best placed to identify relevant opportunities to use digital solutions to meet stakeholder needs (4). A recent survey of HCPs found that patient outcomes and real-world evidence are among the most important criteria considered when prescribing (5). Both of these criteria are increasingly influenced and enhanced by digital technology. Patients with access to vast amounts of health information are more informed and empowered than ever. Medical affairs teams can employ digital solutions to engage with and enable patients and advocacy groups to play an important role in their care, while also generating valuable insights about how to develop better therapies and other relevant support solutions.

CRC’s experienced Medical Affairs team has the expertise to plan and implement digital collection and analysis of real-world data as part of a strategic medical communications program designed to optimise our clients’ commercial success.

References:

1. Plantevin, L. et al. Reinventing the Role of Medical Affairs. 2017. PharmExec. Available at: https://bit.ly/2fz81dF
2. Comstock J. 56 digital health mergers and acquisitions in 2018. MobiHealthNews. Available at: https://bit.ly/2SZyClY
3. Muoio D. Roche acquires oncology EHR company Flatiron Health for $1.9B. 2018. MobiHealthNews. Available at: https://bit.ly/2Rz9TrY
4. Devoy, M. Digital Health: The Road Ahead for Medical Affairs. 2018. Elevate Magazine. Available at: https://bit.ly/2TILDAt
5. Plantevin, L. et al. Reinventing the Role of Medical Affairs. 2017. Bain & Company. Available at: https://bit.ly/2TGtmUl

The burden of cancer is increasing globally, making the search for new oncology therapies a major priority for the research community and a consistent area of investment for pharmaceutical companies. In 2018, over 138,000 people in Australia were diagnosed with cancer and over 48,000 people died from cancer (1). There were approximately 130 cancer treating medicines available on the Pharmaceutical Benefits Scheme (PBS) in 2018, of which 70 have been approved since 2013 (2). This is an indication of the accelerating pace of new drug discovery in oncology bringing new therapeutic options to healthcare professionals (HCPs) and patients. However, this deluge of new therapies can also leave HCPs, patients and payers with many questions around how these therapies perform in real world clinical practice.

The Evidence Gap

Randomised controlled trials (RCTs) are the gold standard for informing regulatory approval of new therapies and expanded indications for already approved therapies. However, they are costly and time intensive and since studies include a limited patient population who meet specific criteria there is often an evidence gap between clinical research data and real world clinical practice outcomes (3). This evidence gap coupled with the increasing need to provide timely access to new therapies, particularly in the oncology space, has led to the need for real world data (RWD). RWD is useful for payers as a supplement to existing RCT data to show the clinical and cost-effectiveness of therapies over an extended time frame.

RWD is data relating to patient health status and/or delivery of health care generated outside of conventional RCTs. This data can be derived from a variety of sources including patient registries, electronic health records (EHRs), insurance data, as well as mobile applications and devices (4). RWE is generated from these data sources and potentially used to inform regulatory and reimbursement decision making. RWE supplements RCT data by providing information on disease progression and overall survival over extended time periods (5). RWE is also useful where large RCTs are not feasible, such as assessment of treatment effectiveness in rare diseases, niche indications and patient subgroups (5).

Closing the Gap with RWE

Many countries have implemented programs for the collection and analysis of RWD via patient registries. Some have also developed strategies for use of RWE to capture information relevant for research and drug discovery, as well as regulatory and reimbursement decisions. For example, in America the FDA recently published a framework for its ‘RWE Program’ to inform the strategic use of RWE to enhance regulatory decision making (6). In England, the National Cancer Registration and Analysis Service (NCRAS) was launched in 2013, which provides comprehensive clinical information on all 350,000 people diagnosed with cancer in England each year, as well as 141 million historical cancer records (5).

RWE in Australia

In Australia, the Therapeutic Good Administration (TGA) has implemented an expedited ‘Provisional Approval pathway’ for the registration of new medicines in certain circumstances such as in the case of innovative cancer therapies (7). Providing timely access for patients to often highly expensive drugs also requires clinical and cost-effectiveness assessment by the Pharmaceutical Benefits Advisory Committee (PBAC) prior to reimbursement listing on the PBS. Although there is no formal framework for the use of RWE in Australia, there have been several instances where the PBAC has requested post-marketing RWD to enhance the clinical and cost-effectiveness evidence for certain cancer drugs to track especially longer term outcomes.

One example of the successful use of RWE involves the immuno-oncology drug ipilimumab for treatment of patients with malignant melanoma, which was approved on the Managed Entry Scheme (MES). Inclusion on the MES involved a risk-sharing ‘pay for performance’ arrangement whereby rebates would be payable should the two-year overall survival rates in real world clinical practice not align with the RCT outcome. To meet this requirement the sponsor collected RWD from consenting patients prescribed ipilimumab over the 2-year follow-up period. In this case, patients’ overall survival, the gold standard endpoint in RCTs, was supported by the RWE.

This is an example of the value of RWE in removing payer doubts around clinical and/or economic effectiveness, thereby benefitting patients through earlier access to subsidised medicines.

CRC’s experienced Medical Affairs team has the expertise to identify and work with key stake holders to understand where evidence gaps exist and develop strategies for generating RWE to inform reimbursement decisions.

References:

1. Australian Government Cancer Australia. All cancers in Australia. 2018. Available at: https://bit.ly/2cfR33K
2. Australian Government Dept of Health. Cancer Fact Sheet. 2018. Available at: https://bit.ly/2DJEefs
3. Chatterjee A., et al. Real-world evidence: Driving a new drug-development paradigm in oncology. 2018. McKinsey&Company. Available at: https://mck.co/2KpCtrs
4. Eastman, P. Potential Value of Real-World Evidence in Lung Cancer Care. 2018. Oncology Times. Available at: https://bit.ly/2R5IVmL
5. Real-World Evidence in Oncology. 2018. IQVIA. Available at: https://bit.ly/2Dus9ds
6. US Food and Drug Administration. Framework for Real World Evidence. 2018. Available at: https://bit.ly/2B0i7ze
7. Kim H., et al. A real-world example of coverage with evidence development in Australia – ipilimumab for the treatment of metastatic melanoma. 2018. Journal of Pharmaceutical Policy and Practice

My Health Record (MHR) is a new secure online summary of consenting individuals’ health information, enabling centralised storage of health documents such as hospital discharge summaries, pathology reports, prescription documents, organ donor registration details and Medicare documents (1). While there are many benefits to implementing MHR, there are also concerns around the secondary use of data, as well as cybersecurity, data errors, risks to patient safety and medico-legal implications for healthcare providers (HCPs).

Aligned with the increasing focus on patient centricity among pharmaceutical and medical device companies, there is a need to access better patient data and develop an improved understanding of the patient journey. In this brave new digital age, electronic health records provide a rich data source of insights about the impact of treatments on patient outcomes. However, there is a disparity between the perception of big data as the ‘holy grail’ for insights and an apparent lack of confidence among consumers and HCPs in committing their information to MHR, given recent public debate.

Benefits of My Health Record

The age of digital healthcare is upon us and many countries have implemented centralised electronic health records systems, similar to MHR, to integrate health data from multiple sources that is accessible by relevant stakeholders. Peak health bodies including the Australian Medical Association, the Royal College of Australian GPs and the Pharmacy Guild of Australia are in support of MHR for its potential to positively impact patient care and support practitioners (2). Australia has approximately 230,000 medication misadventures a year costing the healthcare system $1.2 billion (3). It is hoped that one of the many advantages of implementing the MHR system in Australia will be a reduction in these costly, often preventable adverse drug events.

The intention is that each individual’s record will eventually be populated with data that provides a complete digital health record in one place that is accessible to all relevant HCPs. With more work, the system should provide timely access to health information which saves vital time in emergencies and allows for more time spent treating patients. Enabling doctors to see a range of clinical, prescription and health information about a patient should reduce medication errors, as well as unnecessary duplication of pathology and imaging tests (4). Community pharmacists will also benefit through access to clinical information in a shared health summary which is useful for performing MedsChecks and Home Medication Reviews (4).

Data Security, Misuse and Medico-legal Concerns

The perceived benefits of the MHR system have been largely overshadowed in the media by concerns around data security and misuse of data. To ease concerns around data privacy, the Australian Parliament introduced amendments to prohibit insurers and employers from accessing records. Only certain government agencies can access records including the Australian Digital Health Agency, the Department of Health and Medicare. Additionally, law enforcement authorities require a court document to access information, all access to the system will be logged and heavy penalties will be imposed on those who access information illegally.

Despite these safeguards, vulnerable communities including those with mental health issues, people with HIV and victims of abuse or domestic violence remain unconvinced that their data will remain secure. The issue of accountability for medical errors caused by incomplete or incorrect data also remains unresolved. Good medical practice relies on accurate information, and in situations where multiple people can enter and edit data the potential for error increases. GPs have raised concerns about the medico-legal implications in situations where treatment decisions based on incomplete or inaccurate information cause harm to a patient (5). Uncertainty remains around medical indemnity, malpractice liability and what recourse is available to patients if mistakes are made.

Nevertheless, My Health Record, is a reality and so it is hoped that the various concerns raised can be resolved over time.

CRC’s experienced Medical Affairs team has the expertise to understand and utilise digital healthcare data for the purpose of demonstrating therapy value and supporting Medical Affairs related projects.

References:

1. What is My Health Record? Australian Digital Health Agency. Accesses 30^th January 2019. Available at: https://bit.ly/2B5N3On
2. Zhou N. My Health Record: privacy, cybersecurity and the hacking risk. 2018. The Guardian. Available at: https://bit.ly/2Ldk8hW
3. My Health Record can help prevent medication misadventures. Australian Digital Health Agency. Available at: https://bit.ly/2HKiUtM
4. Margo J., My Health Record: the benefits and risks explained. 2018. Australian Financial Review. Available at: https://bit.ly/2CUn0Ns
5. GPs raise fresh concerns about the legal risks of My Health Record. 2019. ABC Radio Interview with Dr Kerryn Phelps. Accesses 31^st January 2019. Available at: https://ab.co/2SiGvpA

Artificial intelligence (AI) is set to bring a paradigm shift to the healthcare industry facilitated by technological advances, the availability of vast amounts of healthcare data and rapid development of big data analytical methods (1). AI systems analyse immense amounts of data from an array of sources to draw connections and predict outcomes which can be applied in several ways to healthcare (1). AI involves the use of software and algorithms to analyse data in a way that aims to mimic processes related to human intelligence such as reasoning, learning and adaptation, sensory understanding and interaction (1, 2).

Different AI techniques can be applied to healthcare data in structured and unstructured formats. Machine learning (ML) is useful for analysis of structured data from diagnostic imaging, genetic testing and electrophysiological data. Natural language processing (NLP) is used to analyse unstructured data such as clinical notes or medical journals by turning text into machine-readable structured data (1). The application of these technologies has great potential to unlock clinically relevant information in healthcare data from multiple sources to assist in clinical decision making (1).

Challenges to AI in Healthcare

There are challenges that must be overcome before the full potential of AI in real-life healthcare applications can be realised including privacy issues relating to the storage, use and sharing of sensitive health data, as well as the lack of adequate regulatory and legal frameworks. In America the FDA has approved a number of healthcare algorithms, however the guidance on how these algorithms are being reviewed and regulated has been described as unclear by industry stakeholders (3).

For example, AI technologies based on ML algorithms that are designed to learn from patient data and adapt as increasing amounts of data are analysed (4). Systems such as this will need to enable sharing of sensitive patient data while keeping protected information safe in compliance with government privacy regulations. A further challenge is developing a framework for how ML algorithms should be regulated and implemented in clinical practice, since these algorithms incorporate ‘new learning’ and adapt in response to increasing amounts of patient data (4).

In Australia, current Therapeutic Goods Administration (TGA) regulations do not adequately capture all ‘Software as a Medical Device’ (SaMD) under the risk-based classification used for medical devices. At present many SaMD products are classified by the TGA as low risk even though the potential risk for users may be higher. Therefore, the regulator will soon be consulting on changes to the regulations relating to emerging technologies including  diagnostic AI systems, as well as health apps and 3D printing of body parts (5).

 AI for Diagnosis of Disease

The first AI-based diagnostic system designed to provide an autonomous screening decision without the need for clinician interpretation was authorised by the FDA in 2018 (3, 6). The technology enables automated analysis of images to detect fluid on the retina for the detection of diabetic retinopathy, which is the leading cause of vision loss in adults. Diabetic retinopathy represents a significant healthcare challenge and will affect an estimated 191 million people globally by 2030. The software provides a quick result indicating that either diabetic retinopathy is present and the patient should be referred to an eye care specialist, or that the screen is negative and should be repeated in 12 months (6). In this case AI provides a result that can be interpreted by a non-specialist, making it feasible that patients could be screened in the primary care setting thus easing the healthcare system burden and potentially lowering costs.

It is increasingly evident that Medical Affairs will have a unique and expanded role in the healthcare industry as digital technologies such as AI transform how healthcare is delivered, as well as how drugs are researched and discovered.

CRC’s experienced Medical Affairs team has the expertise to provide tailored strategic solutions and communicate the value of clients’ products that incorporate artificial intelligence and other new age digital healthcare innovations.

References:

1. Jiang F., et al. Artificial intelligence in healthcare: past, present and future. 2017 Stroke and Vascular Neurology.
2. Is There a Role of Artificial Intelligence in Medical Affairs? 2018 MarksMan Healthcare. Available at: https://bit.ly/2TKBlQr
3. Muoio D. Roundup: 12 healthcare algorithms cleared by the FDA. 2018 Mobihealth News. Available at: https://bit.ly/2qQd0w4
4. Teich D. Artificial Intelligence (AI), Healthcare and Regulatory Compliance. 2018 Forbes. Available at: https://bit.ly/2QMwPim
5. Regulation of Software as a Medical Device. 2018. Available at: https://bit.ly/2CmzQAE
6. Muoio D. FDA permits marketing of AI software that autonomously detects diabetic retinopathy. 2018 Mobihealth News. Available at: https://bit.ly/2syIojH