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European Biopharmaceutical Review
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Developability is increasingly becoming a key area of attention to
optimise efficiency and success during biopharmaceutical development.
Designing and selecting appropriate lead candidates with the desired
quality attributes can have a big impact in reducing attrition and costs
associated with the development of new drugs
The pharmaceutical industry is currently crippled by the increasing cost
of drug development – today’s figures suggest that developing a new
drug costs, on average, many billions of dollars – combined with a
reduction in R&D productivity and the pressing need for new
treatments to be cost effective (1-3). The high attrition experienced
during drug development has prompted the use of the term ‘valley of
death’ to refer to those pre-clinical and clinical stages of development
where most of the casualties occur (4). In this context, new
front-loading, de-risking approaches to drug development are urgently
needed in order to reduce failure in later stages of development, where
associated costs are considerably larger (5).
Bioprocess development remains a central area of risk, not only because
of its impact on the final cost of goods but, more importantly, because
of its influence in key aspects of product quality, biological activity
and safety. Still, the existing divide between discovery and development
functions is posing far too great an obstacle to achieving efficient
drug development (6). Furthermore, from a quality perspective at least,
traditional bioprocesses are essentially ‘passive’ as their quality
management is largely limited to measuring and reporting the output of
the process, rather than driving the design or engineering the input to
obtain a desired outcome. However, in recent years there has been a
progressive shift in the perception of how bioproduction and early drug
development should be articulated in order to address all these
challenges. Some of the strategies include faster and more agile
development, the integration of discovery and early process development
inputs into drug design, or better predictability of bioprocesses and
their output (7).
Developability in Drug Development
Developability is a concept originated in the early 2000s to define the
suitability of a given therapeutic candidate to be developed
successfully as a drug. Initially used in small-molecule APIs, it paid
attention fundamentally to aspects of manufacturing, formulation,
bioavailability and pharmacology, as well as toxicology and, among other
things, sparked the development of new computational predictive
approaches to address aspects of pharmacology and toxicology (8).
In recent years, the developability concept has started to take off in
biopharmaceutical drug development. The main causes behind this are: the
complex and largely unpredictable biomanufacturing processes; quality
concerns and their impact in drug safety and product recalls; and the
a-priori inscrutable outcome of clinical trials.
Developability assessment aims to understand the determinants of product
quality, safety and efficacy, and can be grouped into three major
categories (see Figure 1):
● Manufacturability: looking at whether the product could be made with
an appropriate yield, and whether it would have an adequate quality
profile and be able to be formulated for the desired route of
administration
● Safety: addressing whether the product could potentially trigger
unwanted immunological reactions, promote the production of anti-drug
antibodies (ADAs) in patients, or show an adequate specificity profile
● Pharmacology/mechanism of action: assessing whether the product could
be delivered via the chosen route of administration at the desired dose
and with an adequate half-life. Additionally considering whether it
would exert the right biological response, what patients could benefit
from the treatment, and at what dosage regime
How to Implement Developability?
There is not a unified framework for the implementation of
developability risk assessments in the early stages of development.
Several platforms are being put forward, but there are two particular
areas that seem to be getting more attention:
● The implementation of novel in silico platforms able to assess large numbers of potential candidates
● The development of surrogate in vitro assays capable of reproducing relevant process or physiological conditions
These two differing approaches show great promise in simplifying the
assessment of therapeutic candidates by increasing dramatically the
flexibility and throughput behind lead selection and optimisation
stages, streamlining the ‘selection of the fittest’ for the given
desired outcome.
Aggregation and Stability
Aggregation is perhaps the single most troubling quality attribute
impacting biopharmaceutical development. Besides its obvious
consequences in process yield, formulability or biological activity,
protein aggregates seem to be an important contributing factor to
reported cases of immune reactions in patients and other safety concerns
(9). For example, aggregates are suspected to be involved in the onset
of some of the ADA responses reported in patients. Recently, aggregates
have also been attributed to pure red cell aplasia (PRCA) observed in
patients treated with recombinant human erythropoietin (10). Other
routes of chemical and physical degradation can also have an important
impact in the stability of a product, including its ulterior
aggregation, and can be linked to safety issues in patients, including
immunogenicity.
New in silico predictive tools are being developed in an attempt to
assess the relative stability and aggregation risks in
biopharmaceuticals. Predictive tools to describe degradation reactions,
such as deamidation, oxidation, or undesired post-translational
modifications, such as unwanted glycosylation, are nowadays broadly
available and can be used as an initial assessment during the product
development cycle. More recently, algorithms have been proposed to
predict the aggregation potential of polypeptides. Although some of
these tools still lack extensive validation in biopharmaceutical
systems, their application to re-engineering biotherapeutics with
improved manufacturability (including reduced aggregation and increased
productivity), has been successfully reported by various groups (7,11).
Parallel to the use of such new, predictive computational platforms,
there is a need for simpler and faster analytics to report aggregation
and other degradation mechanisms. Aggregation is a complex phenomenon
that is not easy to describe in its entirety by a single experimental
methodology. Furthermore, many of the existing technologies are not
simple to implement or can be significantly time consuming. The use of
particle imaging technologies or immunological assays are just a few
examples of methods that could potentially offer a sufficiently large
throughput for an early aggregation assessment or formulation study
(12,13).
Formulation and delivery are areas of growing importance in
biopharmaceutical development. There is a growing demand for molecules
that can be formulated for more patient-friendly uses, and subcutaneous
self-administration is a particularly attractive approach, especially
for drugs that require chronic administration or multiple cycles of
treatment. Many biotherapeutics, particularly monoclonal antibodies,
often require administration at relatively large doses. For example,
formulations of 150-200mg/mL are frequently required in subcutaneous
administration because of volume limitations. Such formulations present a
number of challenges in terms of stability, aggregation and viscosity.
This is where a suitable formulability assessment could help identify
candidates compatible with a required route of administration. In silico
platforms able to predict aggregation and stability, combined with
novel high-throughput analytical platforms, show great promise (7,14).
Immunogenicity Assessment
As most therapeutic proteins can be degraded to single amino acids, the
main safety concerns for biopharmaceuticals are usually immune reactions
or exaggerated pharmacology. Immune reactions to biopharmaceutical
administration can be diverse in their nature and impact. In benign
cases, production of ADA might not substantially affect the efficacy of
the treatment, or perhaps only alter the pharmacology of the drug. In
other occasions, however, ADA responses can neutralise the drug and
render the treatment inefficacious. In more extreme cases, immune
responses can take the form of hypersensitivity, anaphylactic reactions,
cytotoxicity or autoimmunity, with severe consequences for the patient
(15). Examples of adverse immunogenic reactions linked to the
administration of biopharmaceuticals include the onset of PRCA in
patients treated with recombinant erythropoietin, or anaphylactic
reactions in patients treated with cetuximab (10,16).
The human immune system is extremely complex in nature and, most
importantly, considerably different from that of animals. Even non-human
primate models present significant variations to human subjects. To
make matters worse, humans show a tremendous genetic variability in
their immune components, particularly in their major histocompatibility
complexes (MHC), which ultimately differentiate the ‘self’ from the
‘foreign’.
As a result of this, regulatory bodies state that animal models are not
good predictors of clinical immunogenicity and therefore do not
recommend their use for pre-clinical safety assessment and put the
emphasis in the careful monitoring of ADA and other immune responses
during the clinical development phases (17).
Recently, new methodologies have been introduced to assess
immunogenicity risks in biopharmaceuticals. In silico tools evaluate the
presence of T-cell epitopes as defined by the interaction of protein
fragments with MHC Class 2 molecules. This type of methodology, albeit
simplifying considerably the antigen presentation process, offers a
privileged insight into the differential T-cell epitope content present
in various therapeutic candidates, and because of its speed and low cost
can be used during lead selection stages to identify molecules with a
lower propensity to generate immunogenicity.
Additionally, ex vivo or in vitro cell-based assays using blood samples
from human donors can provide very powerful information around
comparability, safety of alternative candidates, or even the impact of
formulation on product immunogenicity. This type of assay is already
commonplace in vaccine development because of its proximity to human
subjects compared with animal models.
Interestingly, regulators are starting to encourage the use of in silico
and in vitro platforms as pre-clinical predictors of immunogenicity
risks (18). By combining these two approaches, biotherapeutics with
known immunogenicity problems can be successfully re-engineered and
potentially re-introduced in clinical development (7). Furthermore, this
type of assay could be extremely relevant in comparability studies and
the development of biosimilars and biobetters (19).
Immunomodulation and Immunotoxicology
Many of the biotherapeutic molecules approved for their clinical use in
human patients have an immunomodulatory effect. As indicated above,
animal models have only limited utility in replicating characteristics
of the immune system of human patients. In fact, one of the main
obstacles to translational research is the disconnect between
pre-clinical animal studies and the clinical reality of patients. This
is why even in cases where rodent versions of the therapeutic candidate
have been utilised, their mode of action might not necessarily replicate
that observed in human subjects. Such reality makes pre-clinical
development highly unpredictable and risky both for patients and drug
developers. An extreme example of this uncertainty is the infamous
clinical trial with the superagonistic anti-CD28 antibody TGN1412, which
resulted in four healthy subjects having to be admitted into intensive
care suffering systemic organ failure and very serious health
complications (20). In recent years, a number of groups have managed to
replicate cytokine release syndrome (cytokine storm) responses in the
lab using cells from human donors (21). This opens the door to the use
of ex vivo cell-based assays to characterise in detail both the mode of
action and the side effects of immunomodulatory drugs. The application
of these methodologies could be very relevant for patient stratifi
cation, identifi cation of relevant biomarkers to be used in clinical
trials, or the defi nition of safe clinical dosing for new drugs (22).
Furthermore, they also support 3R initiatives in reducing the use of
animal experimentation.
Designing Quality and Safety
Although there is still substantial room for improvement, cost of goods
(COG) is no longer a signifi cant contributor to the total drug pricing
for most established classes of biopharmaceuticals. In fact, the lion’s
share of drug prices comes from the absorption of costs derived from the
growing attrition and development failures. A focus on quality is
replacing COG as the main paradigm in biopharmaceutical development.
Quality affects essential aspects of drug safety, process robustness,
and even biological activity that can make a difference between the
success and failure of a new product.
So can we move beyond current exemplifi cations of quality by design
(QbD) in process understanding and control, as defined in existing
guidelines, and take them towards designing a desired quality target
product profi le (QTPP) from the start? Developability methodologies can
indeed be used to this end. Not only can they screen out candidates
that might present difficulties or complications in terms of
manufacturability, quality and safety, but they also make it possible to
engineer products with desired quality attributes from the outset. Such
an approach has been successfully implemented in a number of
biotherapeutics with existing stability and safety issues; it points to a
new way of designing biotherapeutics where de-risking methodologies are
at the forefront of the discovery and development process to maximise
success and minimise costs (7).
Developability Workflow
Figure 2 shows how a developability workfl ow could be structured. Early
risk assessments using the methodologies described above can be
utilised before committing to host development. Candidates classified as
‘low risk’ can then move into process development stages, whereas those
classified as ‘high risk’ can be subject to a number of risk-mitigation
strategies depending on where they are in development, or the type of
risk identified and its impact. In cases where programmes are still in
early stages of development, the selection of an alternative candidate –
for example, from display or affi nity maturation libraries – can be an
ideal solution. Alternatively, molecules can be subjected to a
re-engineering programme that can very rapidly produce new, improved
candidates with the desired properties. In cases where this is not an
option (‘late stage’ programmes) processes need to be developed to
address the nature and extent of the risk. It is important to note that,
although process design can be powerful in modulating product yields
and quality, there is only so much process tweaking can accomplish,
particularly when dealing with diffi cult molecules. This work can, in
fact, be lengthy and expensive, and might not be able to achieve a
desired outcome: an example of this would be a stable high-concentration
formulation or a non-immunogenic alternative.
Conclusion
To many, manufacturing development is still primarily about a necessary
evil that every candidate needs to go through in order to enter clinical
development for safety and efficacy validation. Still, there is far
more to bioprocessing that meets the eye. The truth is that, although
molecules belonging to the same class obviously share similar behaviour,
a single amino acid replacement in a molecule can cause havoc in
bioprocessing and in the patient. More importantly, many essential
aspects relevant to candidate success are not directly related to their
‘binding’ activity, but to quality, safety, delivery and compliance
aspects. Unfortunately, these are often not properly addressed during
discovery and early development stages.
In this context, there are two main questions to be asked: “What is the
value of quality?” and “Is it then worth investing in risk assessment
and management strategies, introducing developability aspects in the
design and selecting biotherapeutic candidates?” One could argue that
quality actually has a great value in drug development and that
developability makes economic sense. This is primarily true because the
probability of failure and its costs are so absolutely staggering that
any measure aimed at reducing failure and increasing efficiency in drug
development will prove effective.
This does not mean that drug developers should ‘indulge’ in examining,
testing and controlling every single quality aspect before moving
forward into the clinic. On the contrary, it is about taking calculated
risks based on knowledge rather than pushing candidates forward and
betting on a final outcome (commercialisation) that nine times out of
ten will never materialise. With better design and ‘filtering’ of
candidates early on, attrition in later stages of development should
ease with a very favourable impact in the generation of better and more
cost-effective treatments.
References
1. Herper M, The truly staggering cost of inventing new drugs. Visit:
www.forbes. com/sites/matthewherper/2012/02/10/
the-truly-staggering-cost-of-inventingnew- drugs
2. Paul SM, Mytelka DS, Dunwiddie CT et al, How to improve R&D
productivity: the pharmaceutical industry's grand challenge, Nat Rev
Drug Discov 9: pp203-214, 2010
3. Pammolli F, Magazzini L and Riccaboni M, The productivity crisis in
pharmaceutical R&D, Nat Rev Drug Discov 10: pp428-438, 2011
4. Butler D, Translational research: crossing the valley of death, Nature 453: pp840-842, 2008
5. Pritchard JF, Jurima-Romet M, Reimer MLJ, Mortimer E, Rolfe B and
Cayen MN, Making better drugs: decision gates in non-clinical drug
development, Nature Rev Drug Discov 2: pp542-553, 2003
6. Rees H, Supply chain management in the drug industry: delivering
patient value for pharmaceuticals and biologics, John Wiley & Sons,
Inc, 2011
7. Zurdo J, Developability assessment as an early de-risking tool for
biopharmaceutical development, Pharmaceutical Bioprocessing 1, 2013
8. Venkatesh S and Lipper RA, Role of the development scientist in
compound lead selection and optimization, J Pharm Sci 89: pp145-154,
2000
9. Rosenberg AS, Effects of protein aggregates: an immunologic perspective, AAPS J 8: ppE501-507, 2006
10. Seidl A, Hainzl O, Richter M et al, Tungsten-induced denaturation
and aggregation of epoetin alfa during primary packaging as a cause of
immunogenicity, Pharmaceut Res 29: pp1,454-1,467, 2012
11. Jameel F and Hershenson S, Formulation and Process Development
Strategies for Manufacturing Biopharmaceuticals: pp329- 347, John Wiley
& Sons, Inc, 2010
12. Zurdo J, Michael R, Stallwood Y, Hedman K and Aastrup T, Improving
the developability of biopharmaceuticals, Inno Pharma Technol 37:
pp34-40, 2011
13. Mahler HC and Jiskoot W, Analysis of Aggregates and Particles in Protein Pharmaceuticals, John Wiley & Sons, Inc, 2012
14. Buck PM, Kumar S, Wang X, Agrawal NJ, Trout BL and Singh SK,
Computational methods to predict therapeutic protein aggregation,
Methods Mol Biol 899: pp425-451, 2012
15. Van De Weert M, Horn Møller E, Immunogenicity of Biopharmaceuticals: pp27-56, 2008
16. Chung CH, Mirakhur B, Chan E et al, Cetuximab-induced anaphylaxis
and IgE specific for galactose-alpha-1, 3-galactose, N Engl J Med 358:
pp1,109-1,117, 2008
17. ICH S6. Visit: www.ich.org
18. Buttel IC, Chamberlain P, Chowers Y et al, Taking immunogenicity
assessment of therapeutic proteins to the next level, Biologicals 39:
pp100-109, 2011
19. Barbosa MD, Immunogenicity of biotherapeutics in the context of
developing biosimilars and biobetters, Drug Discov Today 16: pp345-353,
2011
20. Suntharalingam G, Perry MR, Ward S et al, Cytokine storm in a phase 1
trial of the anti-CD28 monoclonal antibody TGN1412, N Engl J Med 355:
pp1,018- 1,028, 2006
21. Weissmuller S, Semmler LY, Kalinke U, Christians S, Muller-Berghaus J
and Waibler Z, ICOS-LICOS interaction is critically involved in
TGN1412-mediated T-cell activation, Blood 119: pp6,268- 6,277, 2012
22. Brennan FR, Morton LD, Spindeldreher S et al, Safety and
immunotoxicity assessment of immunomodulatory monoclonal antibodies,
mAbs 2: pp233-255, 2010
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