Introduction: high level abstract elements like diagnostics, prognostics and

Introduction:

Currently, prescribing medical
interventions and drugs works on the basis of there being such a thing as an
‘average patient’. Predetermined doses based on either age, weight or severity
of illness are utilised and thrown like darts at a patient’s condition. Doctors
have had to work on the assumption that one size fits all and the recent figures
regarding ineffective treatments and adverse events reveal this to be untrue
(figure 1).

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Fig
1. Percentage of patient population for whom a drug is ineffective (Spear et al.,
2001)

 

The mapping of the human genome in
2003 and the resulting advancement of the field of pharmacogenomics has opened
a Pandora’s box of understanding regarding treatment and response. It has led
to a greater understanding of disease, its cause and its course and the reasons
behind why some people benefit more than others from treatments as well as to
why some people suffer adverse reactions. It has led to better, more targeted
therapies which is now pointing us toward a ‘cures’ model as opposed to a
‘treatment’ model. 

Personalised medicine recognises those
innate differences in people’s genes, their lifestyles and their surrounding
environment. The overall goal of personalised medicine is to target the right treatments
to the right patients at the right time (Stone, 2016). Taking this into account from
numerous literature reviews, personalised medicine seems to be multi-layered
with varying opinions on what constitutes personalised medicine as well as
numerous elements incorporated into its framework. Figure 2 gives a basic compilation
of the elements which have been placed under the catch all ‘Personalised
Medicine’ from the vast and varied pieces of literature.  From more high level abstract elements like
diagnostics, prognostics and environmental/demographic algorithms to more
specific areas such as orphan drug manufacture and the branch of advanced
therapeutic medicinal products I believe ‘Personalised Medicine’ to be an
umbrella under which many disciplines must intertwine and flow for a successful
patient outcome.

 

Fig.
2 Breakdown of elements cited as being integral to Personalised Medicine (FDA,
2013; Flory and Reinhardt, 2013; Jeelani et al., 2014; Redekop and Mladsi,
2013; Vogenberg et al., 2010)

So what are the benefits of
personalised medicine?

·        
Creating a paradigm shift from the traditional approach of reactive
medicine to preventative medicine

·        
Ensuring treatments and therapies are more targeted to the
individual

·        
Tailored medicine and resulting predictive responses can reduce
the rate of adverse events

·        
Putting the patient at the centre of their treatment could lead to
greater adherence to a treatment (patient buy-in)

·        
One time successful therapies can reduce the overall cost of an
individual’s treatment plan

The paradigm shift

The
field of Personalised Medicine has the potential to shift treatment to a preventative
model by applying a risk based approach to healthcare screening. The ability to
screen for biomarkers, even before a disease starts to express itself, will
allow for early and tailored intervention with a more positive prognosis for
the patient e.g. in the area of breast cancer screening.  In 2012 there were approximately ten or more
types of breast cancer identified each of which respond to different types of
treatments (Curtis
et al., 2012)
this work underlines the heterogeneity of cancer at the genomic level.

Targeted Treatments

The use of
diagnostic tests that seek to qualify specific molecular characteristics
present in a patient allows doctors to choose the most efficacious treatment.
In doing so the costly throwing darts approach can be avoided thereby improving outcomes and
increasing the safety profile by reducing the incidence of adverse events.
Targeted therapies informed by use of biomolecular testing have been developed
and are being used in a number of disease areas such as (PMC, 2017):

–         
Breast cancer

–         
Melanoma

–         
Prostate Cancer

–         
Colon Cancer

 

Reducing the Rate of Adverse Events

 

Reducing
the rate of adverse events is one of the key beneficial outcomes of
personalised medicine. According to figures in a recent FDA document an
estimated 2.2 million ADR’s occur each year in the US with a mortality rate of
100,000 people (FDA, 2013). Many of the
problems arise from how the drug is metabolised by the individual patient. In
cases where the drug is slower at being metabolised the patient runs the risk
of drug toxicity due to them being unable to effectively eliminate the
treatment from their systems. The opposite is then true for an individual that
metabolises the drug quicker therefore eliminating the treatment before any
beneficial therapeutic effect is realised. The discipline of Pharmacogenomics
assists doctors in predicting safe and efficacious dosage for patients based on
their genetic profile.

 

Greater Patient Adherence

 

Tailoring
the treatment to the patient leading to more effective response to disease and
fewer side effects will naturally lead to the patient adhering more stringently
to the treatment regimen. In a recent literature review of patient compliance
rates adherence was found to be higher in groups with a positive genetic marker
outcome compared to the negative groups (Schneider and Schmidtke, 2014).

 

Reducing the overall cost of healthcare

 

The overall
cost of healthcare can see savings with the evolution of more efficient and
sustainable treatment plans.  With the
adoption of Personalised Medicine historical inefficiencies can be eradicated.
As detailed above by moving from reactive medicine to preventative medicine
diseases can be caught much earlier in their cycle therefore reducing the cost
of treatment. The practice of dosing by guess work as well as adverse drug
reactions could all be a thing of the past. Reimbursement can be made more
transparent from the point of view of value proposition for a treatment therefore
enabling the more effective organisation of patient care (Jakka and Rossbach, 2013).

 

Progressive
Innovation

Advances
in technologies and analytical innovations have led to a wealth of scientific
tools being made available to further the progress of Personalised Medicine.
These tools are being utilised to rapidly expand the amount of personalised
treatments available year in year out. Figure 3 shows the number of
personalised treatments growing exponentially from 5 in 2008 to 132 in 2016 (PMC,
2017).

Fig. 3 The number of Personalised
Treatments from 2008-2016

Fields
such as:

–         
Epigenetics

–         
Genome Sequencing

–         
Immunotherapy

–         
Gene Therapy

–         
CRISPR editing

And
of course many more innovations in the future will all combine to advance
Personalised Medicine even further year in year out.

Overcoming
New Drug Candidates Failing Clinical Trials

According
to Tufts Centre for the Study of Drug Development to current cost of attaining
Market Authorisation for a drug is approximately $2.6bn. This overall cost is
split into two main areas –

1.      
Direct Costs of $1.4bn

2.      
The cost of failure of other candidates in the process ~$1.2bn

Recent
figures from BIO have quoted the failure rate of drug candidates to be one in
every ten (BIO,
2016).
As a result Pharmaceutical companies have had to revisit the drug development
process in a bid to reduce costs and overcome this high attrition rate. Drug
developers are starting to shift the founding principles behind Personalised
Medicine into the drug discovery process by adopting the following:

–         
Discovering and validating suitable Biomarkers

–         
Using tools for better stratification of the patient population
for clinical trial recruitment

–         
Implementing more transparent electronic trial management systems

Whilst
the industry failure rate stands at one in ten, the failure rates in the Alzheimer’s
field is much higher with 99.6% of all potential treatments failing to reach
the market.  Recent failures in Merck’s
EPOCH trial and Eli Lilly’s solanezumab, due to no observable clinical benefit
in Phase Three trials, have further underlined the need for better lead and
target validation in the earlier stages of the drug discovery process. Luckily
both of these companies are large enough to absorb such late stage hits but
smaller companies, which are essential to drug discovery, would not survive
such a setback (Lo,
2017).

The
FDA recently released a paper entitled ’22 case studies where Phase Two and
Phase Three Trials had divergent results’ the main theme arising from the paper
was that, as the patient treatment base widened, the results from the trials
started to get more unpredictable. This, on its own, points to a greater need
for more refined patient selection and stratification (FDA,
2017b).

In
a 2014 paper submitted to Nature magazine Astra Zeneca performed a critical
analysis of all failed drug candidates in the five years from 2005-2010. Within
it they outlined ‘the five determinants of clinical success – The 5 R’s’ (Cook
et al., 2014)
which they have now applied to all R projects going forward.  These were:

–         
The Right Target

–         
The Right Patient

–         
The Right Tissue

–         
The Right Safety

–         
The Right Commercial Potential

Adopting
these principles has the potential to increase the probability of success by
way of honing in on more focused and stratified patient subpopulations. This in
turn has the potential to expedite clinical trials and increase the likelihood
of exhibiting better efficacy data.

Government Response

In
the US in particular the previous administration recognised the many benefits
that could stem from the field of Personalised Medicine. In 2015 Barack Obama
announced the ‘Precision Medicine Initiative’ which set the foundation for the
resulting 21st Century Cures Act. This 1000 page law was enacted in
December 2016 and within it the FDA has been granted $500 million in additional
funding to cover the costs in implementing certain sections of the law.

Presently
the price of medicines is dictated by the overall costs it takes to bring the
treatment to the market. This greatly limits accessibility to large cohorts of
people that require access to such medicines. 
The FDA has become mindful of the fact that the regulatory burden they
place on manufacturers of pharmaceutical products can inflate the price of the
resulting treatment.

As
part of their new mandate through the Cures act the FDA are seeking to apply a
risk based approach to regulation. The act will provide the FDA the resources
necessary to modernize both itself and its regulatory programs. The ultimate
goal is to ensure access to safe and efficacious new treatments that are
affordable to the general public.

In
2017 the FDA announced a detailed work plan with step by step deliverables for
the Cures act. The following is a summary of the work plan deliverables (FDA,
2017c):

–         
Subtitle A, Patient Focused Drug Development

–         
Subtitle B, Advancing New Drug Therapies

o  
Qualification of Drug Development Tools

o  
Targeted Drugs for Rare Diseases

o  
Reauthorisation of Program to Encourage Treatments for Rare Paediatric
Diseases

o  
Grants for Studying Continuous Manufacturing

–         
Subtitle C, Modern Trial Design and Evidence Development

o  
Novel Clinical Trial Design

o  
Real World Evidence

o  
Protection of Human Research Subjects

o  
Informed Consent Waiver or Alteration for Clinical Investigations

–         
Subtitle D, Patient Access to Therapies and Information

o  
Summary Level Review

o  
Accelerated Approval for Advanced Regenerative Therapies

o  
Standards for Regenerative Medicine and Regenerative Advanced
Therapies

o  
Combination Product Innovation

–         
Subtitle F, Medical Device Innovation

o  
Breakthrough Devices

o  
Humanitarian Device Exemption

o  
Recognition of Standards

o  
Institutional Review Board Flexibility

o  
Least Burdensome Device Review

o  
Clarifying Medical Device Software

–         
Subtitle G, Improving Scientific Expertise and Outreach at FDA

o  
Inter Centre Institutes

(note – there seems to be an
omission of subtitle E in the source FDA document)

It
is hoped that by implementing the above work plan the FDA will satisfy the
requirements set out within the Cures Act which in turn will pave the way for
bringing new and innovative treatments to the market in a more efficient and
cost effective manner.

Biomarkers and Diagnostics

“We
are pleased to see substantial progress and look forward to continuing our
efforts to advance biomarkers, which will help bring additional, important new
therapies to patients in need.” Janet Woodcock, M.D., Director, Centre for Drug
Evaluation and Research, FDA

According
to Tufts, 42% of drugs currently in development have used biomarkers in their
R design. The Tufts report also detailed that Biopharma companies have
doubled investment in PM since 2010 and will seek to increase this by a further
33% by 2020 (Tufts,
2015).

Greater
productivity within drug development pipelines can be realised through the
combination of Personalised Medicine and Biomarkers. This can be achieved by
way of ascertaining the best treatment response in each individual patient. From
the BIO study it can be seen that greater success has been achieved in programs
that use Biomarkers through each and every Phase from Discovery through to Phase
Three trials (BIO,
2016).
The main obstacle facing greater adoption of this combination approach is the
cost company’s face in reaching the requisite understanding of immune response
that is required in order to identify reliable Biomarkers.

As
can be seen from the Astra Zeneca study, failure in its totality is not a bad
thing, indeed both progress and innovation spring from failure. Through
informed science, carefully compiled clinical trial protocols as well as
concisely stratified clinical trial populations greater success can be realised
for new drug candidates seeking market authorisation.

Moving Personalised Medicine Forward

 

In order for Personalised Medicine to
move forward International collaboration will be required to keep up with the
pace of progress in science and technology. 
As it currently stands there are a number of barriers to capitalizing on
this new field of medicine:

 

–         
Regulatory Constraints

–         
The quagmire surrounding reimbursement

–         
The difficulties surrounding the practical
application of new medical techniques in the clinical setting

The
rapid pace of Personalised Medicine has already seen a number of treatments
approved by the FDA that are tailored to an individual’s genetic profile or, in
the case of cancer treatments, the genetic profile of the tumour itself.
Patients undergoing treatment for cancer now receive molecular testing as part
of their treatment pathway which in turn allows the doctor to choose a
treatment with the greatest individual response and also reduce the risk of
exposure to an adverse event (FDA,
2017a).

Regulatory Constraints

Whereas
in the past regulations were put on place to protect the general public from
tragedies (sulphamidazole elixir?? and thalidomide) authorities like the FDA
and the EMA now recognise the value of Personalised Medicine and their own role
in expediting these treatment to patients. The release of the 2013 FDA document
‘ Paving the way for personalised medicine – FDA’s role in a New Era of Medical
Product Development’ (FDA,
2013)
was the starting point in the FDA underlining their dedication to advancing
medicine and commitment to aligning their activities to achieve more seamless
market authorisation for Personalised Therapies. The agency has established a
number of new departments as well as a number of guidance documents
specifically to facilitate the advancement of personalised medicine. Figure 4
details each one of the FDA guidance’s pertaining to Personalised Medicine that
have come into place from 2005 to 2017 (utilising the 2013 document for data
from 2005-2013 and the FDA website for 2014-2017). As can be seen a lot of
resource has gone into the area underlining the FDA’s dedication to provide the
guidance’s necessary to attain approval.

 

2005

Pharmacogenomic Data Submissions

2007

Pharmacogenomic Tests and Genetic Tests for Heritable Markers

2007

Statistical Guidance on Reporting Results from Studies
Evaluating Diagnostic Tests

2008

E15 Definitions for Genomic Biomarkers, Pharmacogenomics,
Pharmacogenetics, Genomic Data and Sample Coding Categories

2010

Adaptive Design Clinical Trials for Drugs and Biologics (Draft
Guidance)

2010

Qualification Process for Drug Development Tools (Draft
Guidance)

2011

Clinical Considerations for Therapeutic Cancer Vaccines

2011

In Vitro Companion Diagnostic Devices (Draft Guidance)

2011

Commercially Distributed In Vitro Diagnostic Products Labelled
for Research Use Only or Investigational Use Only: Frequently Asked Questions
(Draft Guidance)

2011

E16 Biomarkers Related to Drug or Biotechnology Product
Development: Context, Structure, and Format of Qualification Submissions

2011

Evaluation of Sex Differences in Medical Device Clinical Studies
(Draft Guidance)

2011

Applying Human Factors and Usability Engineering to Optimize
Medical Device Design (Draft Guidance)

2012

Enrichment Strategies for Clinical Trials to Support Approval of
Human Drugs and Biological Products (Draft Guidance)

2012

Factors to Consider When Making Benefit-Risk Determinations in
Medical Device Premarket Approval and De Novo Classifications

2012

The Content of Investigational Device Exemption (IDE) and
Premarket Approval (PM A) Applications for Artificial Pancreas Device Systems

2013

Mobile Medical Applications

2013

Clinical Pharmacogenomics: Premarket Evaluation in Early-Phase
Clinical Studies and Recommendations for Labelling

2013

FDA Decisions for Investigational Device Exemption (IDE)
Clinical Investigations (Draft Guidance)

2013

Molecular Diagnostic Instruments with Combined Functions (Draft
Guidance)

2013

Providing Information about Paediatric Uses of Medical Devices
Under Section 515A of the Federal Food, Drug, and Cosmetic Act (Draft
Guidance)

2013

Submissions for Post approval Modifications to a Combination
Product Approved Under a BL A, NDA, or PM A (Draft Guidance)

2013

Current Good Manufacturing Requirements for Combination Products
Final Rule

2014

Qualification
Process for Drug Development Tools
(final
guidance)
 

2014

In Vitro Companion Diagnostic Devices
(final guidance)

2014

Framework for Regulatory Oversight of Laboratory Developed Tests
(LDTs)
(draft guidance)

2014

FDA Notification and Medical Device Reporting for Laboratory
Developed Tests (LDTs)
(draft guidance)

2016

Use of Standards in FDA Regulatory Oversight of Next Generation
Sequencing
(NGS)-Based In Vitro Diagnostics (IVDs) Used for Diagnosing
Germline Diseases
(draft guidance)

2016

Use of Public Human Genetic Variant Databases to Support
Clinical Validity for
Next Generation Sequencing (NGS)-Based In Vitro Diagnostics
(draft guidance)

2016

Principles for Co-development of an In Vitro Companion
Diagnostic Device with a
Therapeutic Product
(draft guidance)

2017

Discussion Paper on Laboratory Developed Tests (LDTs)
(discussion paper)

Reimbursement

The
adoption of Personalised Medicine as a treatment option available to all will
depend on governments and payers seeing a benefit from this new Healthcare
paradigm. They must set about creating new value frameworks that are more
tailored to uncovering the cost benefit of such treatments and shifting the
goal posts on what constitutes value in the healthcare setting. As can be seen
from earlier in this paper Personalised Medicine reaps many benefits including
disease prevention, a decrease in disease progression, reduce adverse events
and resulting hospitalisations and a decrease in costly interventional/invasive
procedures. Greater efficiencies can be realised by ensuring only patients that
will benefit from a particular treatment will be in receipt of it.

Adoption in the clinical setting

A
survey completed in 2016 (Miller
et al., 2016)
showed that only four in ten consumers were aware of the existence of
personalised medicine with only 11% of patients being offered a personalised
treatment. The integration of Personalised Medicine into day to day healthcare
will require the following (PMC,
2017):

–         
Education of the public and creating awareness of personalised
medicine and this new treatment approach

–         
Putting the patient at the centre and engaging them in their
treatment

–         
Better healthcare information management systems

–         
Recognition of molecular diagnostics as a valuable tool in guiding
treatment

–         
Revisiting how the overall package could be delivered – e.g.
infrastructure, dedicated clinics

Conclusion

It
has been said at the outset and now in conclusion that the goal of personalised
medicine is to provide “the right treatment to the right patient at the right
time” (Stone,
2016).
The combination of genetics along with other environmental and epidemiological
information will help to determine the susceptibility, prognosis and response of
an individual to a personalised treatment. The mapping of the human genome shed
light on new areas in the effort to prevent, detect and ultimately treat
disease. As technology advances so too will Personalised Medicine in ways that
are as unimaginable to us now as before. For this reason, it is possible that
the elements involved in personalised medicine will change and evolve as more
and more discoveries are made.