moving from preclinical to clinical.pdf

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Drug development is a tough place to be at the moment because of rising costs, falling productivity, lengthening timelines and rising attrition rates. Between 1994 and 2004, investment in drug development rose about 70% but the number of drugs launched fell 40% (1).A 2004 FDA report found that the year 2000 marked the beginning of a slowdown in submissions of new drugs (including biologics) despite increasing levels of basic biological knowledge (2). In 2000-2002, it cost as much as $1.7 billion to bring a drug to market (rising from $1.1 billion in 1995-2000). Despite all the money spent, only a small percentage of the drugs that move into Phase I trials actually reach the market, and only about 2 in 10 of these marketed drugs will recoup the R&D costs (1).Timelines are also increasing—the time taken for drug development (from patent to market) has risen in the U.S. and Europe, from an average of 9.7 years for launches in the 1990s to 13.9 years for launches in the 2000s (2).

DiamonD SponSorS:

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OctOber 2012

by Suzanne elvidge editOr /// Fiercebiotech

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Moving from

Preclinical to clinical

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attrition rateS in drug developmentThe attrition rates in pharmaceutical R&D between 1990 and 2004 in Europe, the U.S. and Japan were 93% in preclinical, 86% in Phase I, 82% in Phase II and 75% in Phase III, based on drugs failing within four years of starting the stage of development. The probabilities of success have also declined over time (2). These high levels of attrition have been blamed for blocking investment in higher risk drugs, drugs for diseases affecting low-income people and countries, and drugs for orphan indications (1).

“With attrition rates as high as 95% from Phase I to registration in oncology, there has to be something wrong with this model,” says Thomas Olin, CEO of Kancera.

The causes of attrition between preclinical and clinical, and in the early stages of

human trials, include a lack of safety and efficacy, issues with pharmacokinetics, little differentiation between the new drugs and the drugs already on the market, and development strategies that move away from the “low hanging fruit” and into more demanding areas of unmet medical need.

“We are increasingly focused on novel biology and chronic slowly progressive diseases, and, consequently, are taking on more technical and clinical development risk,” says Shelia Violette, senior director of translational medicine at Biogen Idec.

The industry needs to improve the odds of getting drugs into clinical trials, let alone onto the market. One approach is to minimize the risk of failure as early as possible, whether that’s by optimizing the candidate drug or by making ”go/no go” decisions simpler and clearer and terminating any drugs that just don’t make the cut as soon as feasible.

tranSlational medicine approacheS—going back to the biologyTranslational medicine, which is often described as “from bench to bedside,” and is the process of moving “from evidence-based medicine to sustainable solutions for public health problems” (3), can have a major role in both drug optimization and program termination by translating and integrating preclinical research into clinical development, providing a sound biological basis for drug development.

Glenn A. Miller, vice president and head of strategy, portfolio and alliances for personalized healthcare and biomarkers at AstraZeneca Pharmaceuticals, says: “The value of translational medicine is that the data leads us in the best direction for future trials.”

Translational medicine starts with understanding the basics of the biology underlying the disease and then finding and

validating predictive and prognostic biomarkers, selecting the best models (in vitro, in vivo and in silico) and working with the right patients for early safety and efficacy studies. Knowing about the basic biology puts the drug development process in context and helps researchers to design clinical trials that ask the right questions.

“Testing your biological hypothesis can often be done quickly and cheaply before spending a fortune on a clinical study,” says Violette. “What needs to change? Companies need to invest in translational medicine studies, and need to learn to ask the right questions, such as ‘what is the biological hypothesis,’ and ‘what do we need to measure.’”

As an example of the effectiveness of this approach, the number of cancer drug approvals improved in 2000 compared with 1991, and this can be attributed

to an increased focus on the biology, pharmacokinetics and pharmacodynamics, zeroing in on absorption, distribution, metabolism and excretion (ADME) characteristics, and correlating these with clinical outcomes (5).

making the moSt of tranSlational medicineTranslational medicine approaches should be put in place early in the drug development timeline, giving

researchers time to understand the biology, and also providing a mechanism for early-stage go/no go decisions, potentially saving or justifying the cost of expensive late-stage animal studies and clinical trials. There are some areas of drug development in which the translational approach is more applicable than others, however—for example, in diseases in which the mechanism of the drug and disease is well understood and the therapeutic approach is simple.

“Integrating translational medicine is much easier when you have a grasp of the mechanism of action of the drug and disease,” says Violette. “It’s also hard to develop biomarkers if you don’t have this information.”

Having a pre-defined approach to translational medicine alone can’t answer everything—for example, some drugs have easily attainable endpoints, and these

“With attrition rates as high as 95% from Phase I to registration in oncology, there has to be something wrong with this model.” ThomaS olin, CEo of KanCEra.

“Testing your biological hypothesis can often be done quickly and cheaply before spending a fortune on a clinical study.”

ShElia ViolETTE, SEnior DirECTor of TranSlaTional mEDiCinE aT BiogEn iDEC.

Biogen Idec’s STX-100 is a humanized monoclonal antibody targeted to integrin αvβ6. It is in early Phase IIa trials for the treatment of idiopathic pulmonary fibrosis (IPF).

The development of STX-100 is based on the biological hypothesis that αvβ6 blockade will reduce TGFβ activity in the lung, and the clinical hypothesis that the reduction of TGFβ activity in the lung will slow or stop fibrogenesis, which should preserve lung function. This pathway is common in fibrotic disease.

The clinical hypothesis is

virtually impossible to test in a Phase IIa that involves only a couple of months of dosing, because Biogen Idec is not dosing a large enough number of patients and for a long enough duration to have a statistically significant impact on lung function. “Instead we can rigorously and quantitatively test the biological hypothesis, using BAL macrophages as biosensors to measure TGFβ activity. This will help us to make a go/no go decision and judge a clinically-active dose,” says Violette.

The Phase IIa trial is expected to complete in early- to mid-2014. l

Case study: STX-100

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don’t necessarily need purely an early-read translational medicine approach, or detailed information about the mechanism of action. It’s all about knowing what questions need to be asked.

“In areas where simple translational medicine studies are not a suitable approach, large consortia trials involving both academia and industry could be appropriate, particularly in areas like cardiovascular disease or diabetes,” says Abbie Celniker, CEO of Eleven Biotherapeutics.

tranSlational medicine approacheS—underStanding the biologyAgain, translational medicine begins with understanding the basic biology of the disease and the drug, and using this information to ask the right questions in preclinical and early clinical trials—a simple and common-

sense process.“Translational medicine has been

around for decades, by moving from basic biology to applied studies. It informs scientists how to develop drugs,” says Lars Ährlund-Richter, chief scientific officer at Kancera.

This approach has perhaps been overlooked in some cases of traditional drug development, which can start by focusing on the niche, creating a target profile of a drug, and building a development plan around this information.

“There can be a focus on validating the target and assessing the toxicity of the drug in preclinical development, without thinking about testing the biological hypothesis,” says Violette.

The FDA is fully behind this approach, with its Critical Path Initiative (CPI). The critical path is defined as the time from the beginning of clinical trials to drug

launch, and the CPI is the “FDA’s national strategy to drive innovation in the scientific processes through which medical products are developed, evaluated, and manufactured” (1; 6).

“You need the best science to educate your drug development,” says Miller.

The CPI aims to cut costs and time of drug development by focusing on specific key areas in drug innovation, including (1):• Better evaluation tools,

including assays and biomarkers

•Streamliningclinicaltrials•Usingbioinformatics•Improvingmanufacturing•Focusingonpublichealth

needs and at-risk populations.

the role of biomarkerS in tranSlational medicineBiomarkers in translational medicine include a variety of different endogenous molecules, such as peptides, proteins, polysaccharides and metabolites, as well as stretches of genetic material. Biomarkers have an important role in translational medicine, and can be divided into three types (1; 5):•Pharmacodynamic—reflecting

the outcome of an interaction

between a drug and its target, confirming that the drug is interacting with the correct target, or pinpointing exactly where the drug is acting if there are a number of potential targets. Pharmacodynamic biomarkers can also help drug development teams select (and discard) lead candidates, or select the most appropriate dose for preclinical or clinical trials.

•Prognostic—reflectingthecourse of disease in an untreated individual, or the patient’s likely outcome irrespective of treatment, separating patients into good and poor outcomes.

•Predictive—stratifyinghow patients will respond to treatment. Predictive biomarkers can act as surrogate endpoints, providing information on the effect of the treatment on the clinical endpoint.

The use of biomarkers in clinical trials has grown between 1991 and 2002 (5). They have an important role in translational medicine—they support researchers in taking interesting findings and moving them from preclinical to clinical, and then to larger groups of patients.

“Predictive biomarkers help us to segment disease into subtypes, and realize that sometimes what we think is one disease is actually two separate diseases in the same location—e.g. EGFR-positive and -negative lung cancer, or different subtypes of neurological diseases within broad categories, such Alzheimer’s disease or depression,” says Miller.

As well as being a useful tool to predict which patients will respond, biomarkers can also be used to

make the go/no go decisions and terminate drug development if necessary (4).

“Using biomarkers in Phase I studies doesn’t remove the risk entirely but gives a quicker ‘read out,’ so you don’t have to wait for Phase IIa to get a feel,” says Graham Dixon, CSO and head of research at Addex Therapeutics.

Dixon’s colleague, Charlotte

Keywood, chief medical officer at Addex, adds: “Biomarkers can be indication-dependent—it’s easier in indications such as diabetes where the biomarker is the same in animals and humans. For some indications, such as CNS disorders and psychiatry, there are few

biomarkers and the animal models aren’t as good, so that is harder, but they do at least give hints on active doses.”

STX-100, Biogen Idec and Stromedix’s humanized monoclonal antibody, is an example of a project that used biomarkers to test the biological hypothesis.

One of the challenges of biomarkers is validating them,

especially if they are to be used as surrogate endpoints, to pinpoint specificity, and sensitivity, and confirm their activity in normal cells and in disease. The process involves making statistical connections between the biomarker in health and disease, or with the drug’s

“Translational medicine has been around for decades, by moving from basic biology to applied studies. It informs scientists how to develop drugs.”

ÄhrlunD-riChTEr, ChiEf SCiEnTifiC offiCEr aT KanCEra.

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efficacy and toxicity in clinical trials, and its links with clinical endpoints (5). The FDA has set up programs to support the use of biomarkers in drug development, with a focus on mapping the processes and criteria needed to validate biomarkers to use as standardized and recognized surrogate endpoints (1).

“Finding biomarkers is a complex and expensive process, so there is a need for collaborations between academia and industry. The advantage of academic research is also that the information on the biomarkers will be available to more than one company, enabling development of a spectrum of drugs for each disease,” says Celniker.

genomicS and proteomicSGenomics and proteomics, and other of the “omics” approaches, have been useful in helping to elucidate the biology of disease, as well as in finding new biomarkers. The Human Genome Project has added to the number of known biomarkers—for example, the Human Genome project completed in 2003, and in cancer, biomarkers rose from around 500 in 2001 to more than 5,000 in 2010 (5).

“Omics is very important—but we need to remember that with omics we are creating the library and we still need to read the books and pull out the information,” says Miller. Violette concurs, saying: “The ‘omics’ are useful, but there can be a lot of ‘data churning’ without stopping to think about how the data will be used.”

Working to StrengthS—multidiSciplinary approacheS and uSing academia

To be fully effective, translational medicine needs to be multidisciplinary, and needs clear communication and close collaboration between scientists and clinicians—the two groups need to learn to think like each other, at least in part.

“Any drug development project should start by talking with clinicians and looking at the target, and even having clinicians as part

of the process,” says Olin.Clinicians can act as a resource

for scientists, as they have the expertise in the areas of disease.

“Having clinical trial experts helping to design preclinical trials can maximize the value of animal experiments,” says Dixon. “It also avoids repetition of effort.” Keywood adds: “It’s all about joining together different disciplines and feeding back to one another.”

Translational medicine also requires collaboration between academia and industry—academic laboratories have access to talented and knowledgeable scientists, who can carry out pre-competitive discovery biology without the same timescale pressures as industry.

“Most advances are based on a combination of academic and industry research,” says Miller. “Therefore it’s vital to collaborate with industry centers and pull it all into an actionable plan.”

Academia can also help cut the

vitro genetic toxicology studies, safety pharmacology studies, general toxicology studies, and the associated analytical studies (formulation and bioanalytical). More recently, however, there has been a dramatic increase in other types of therapeutics (e.g., biopharmaceuticals, imaging agents, botanical products, and others) and in these situations the “standard” approach was inappropriate to achieve approval for an investigational new drug (IND). This was the result of such factors as:

•Selectioncriteriafortheappropriate animal species to be used in testing

•Immunogenicityconcernsdue

to a lack of homology between the therapeutic and the animal species used for testing

•Theneedtogenerate limited human data as part of the drug selection process

•Therapiesthataredesignedtobeadministered for limited lifetime use in humans

•Therapiesforlife-threateningindications or serious diseases where effective therapy is

currently unavailable or has limited effectiveness

•Physiochemicalpropertiesoftherapeutics that justify the elimination/revision of specific studies

MPI Research has conducted thousands of efficacy and safety studies for small molecules and biopharmaceuticals, as well as medical devices. As a company, we work to maximize quality and efficiencies on behalf of our Sponsors’ regulatory applications. In partnering with our pharmaceutical and biotechnology Sponsors in designing studies required for the development of their particular therapeutic, we can say with confidence that based on the amount of experience contained with MPI Research there isn’t much that we haven’t seen. Our goal is to improve the odds for Sponsors to select the right lead candidates, and to conduct the right studies in the right way, taking into consideration all factors to ensure their IND submissions are successful. Contact us at [email protected] to learn how we can help you achieve your drug and device research goals. l

The primary challenge for pharmaceutical and biotechnology companies in developing their drugs and medical devices is to carefully assess the relationship between efficacy and toxicity before entering into human clinical trials. Nonclinical testing is required to establish both the efficacy of a new therapeutic as well as a safe starting dose for the initial human clinical trials.

MPI Research realizes the development of novel therapeutics can be as diverse as the classes developed within the industry. We also understand how important it is to design a nonclinical program tailored specifically to the therapeutic that our Sponsors are developing. There is not a “once size fits all” approach for therapeutics, and to design the right approach requires experience and regulatory knowledge of the various approaches that are critical to improve the odds of successfully moving into the clinical phase.

For many years, the majority of new therapeutics in development involved small molecules designed to interact with cellular receptors. The nonclinical studies conducted to support the progression of these products into Phase I became a “standard approach” for drug development and involved the following: in

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attrition rate where it’s caused by lack of biological knowledge.

“Only basic science makes the big leaps forward—but it has to be science of the best quality,” says Thomas Helleday, professor of translational medicine at Karolinska Institute. “However, in return, industry needs to improve access to molecules, with more generous material transfer agreements [MTAs].”

Validating tools, such as biomarkers, used in translational medicine can be time-consuming, and because academia doesn’t always have the same time pressures as the industry, it can be better placed to work on these projects.

“Many small companies don’t have the money to research the basic science—they have to focus on the product and reaching milestones,” says Helleday.

Academic researchers are also sometimes better situated to ask ”bold questions.”

“Academics have the disease rather than the product in mind, and do not have to conform to strict industry goals,” says

Helleday. “They can work with crowdsourcing and open innovation, and can take greater risks.”

However, as much as industry needs academia, academia also needs industry because though academics can initiate drug development projects and validate them in preclinical and even early clinical trials, they are rarely set up to optimize drugs and can’t get products onto the market.

aSking the right queStionS and uSing the anSWerSUnearthing the biological hypothesis at the early stages of drug development can improve the success rates in moving drugs from preclinical to clinical development, but this involves asking the right questions of both the scientists and clinicians.

“The main focus of translational medicine is being able to identify the right information and the right route. It’s about taking a step back and looking at the bigger picture,” says Miller. “Think about what the goal of the project is, and work out the key steps and the right approaches to get enough data. However, balance is important, too—the balance between wanting to know everything and having enough to make the decision. The challenge then is to translate the enormous amount of information into something that is of benefit.”

The key steps involved are to define the biological and clinical hypotheses, and then to design clinical studies to test these hypotheses in a rigorous fashion. To do this, different questions need to be asked at different stages, and they need to be tailored to the characteristics of the drug.

“In preclinical studies, we look for mechanism of action and dose, and in clinical trials, we want to know which patients will respond and which patients could take part in clinical trials to speed up approval,” says Celniker.

By triggering an early go/no go decision, translational medicine can cut the costs of drug R&D, but it’s important to act on the answers that you get.

“If you are taking translational

medicine seriously, you need to be willing to live or die by the results—if an early clinical trial that rigorously tests the biological hypothesis is negative, it can minimize later losses,” says Violette.

tranSlational medicine approacheS—aiding the move from animalS to humanSUsing animal models in drug testing has always faced some controversy,

from the perspective of animal rights to the ability of animal models toreflectdiseasestatusinhumansaccurately.

“Animal models can only represent so much—sometimes studies in animals can kill a product that could have been effective, or allow through a product that’s ineffective or toxic in humans,” says Keywood.

Because of this, it’s important for institutions to continue developing animal models, and for researchers to use composites of the best and most relevant models. There are aspects of animal models that can still be improved by understanding the clinical system and then applying this back, and there are a number of different approaches to this. As an example, many animal studies in cancer use xenografts—human tumors transplanted into mice.

“One issue with cancer xenograft models is that only a minority of cells engraft into the animal, and these aren’t always representative of the tumor. Another issue is that the human tumor does not end up in the relevant microenvironment. Our vision was to create a model that was more similar to a Phase II situation, by growing human stroma [the supportive tissue] in the animal and then transplanting the tumor,” says Ährlund-Richter. “In principle, one could create models that represent individual humans and their tumors.”

These can be described as mouse ”stand-ins” or ”avatars,” and can also represent an individual’s immune system, microbiome, or other characteristics (8; 9). These could be more predictive of a drug’s development potential, but it is still early, and there is no guarantee

that the mechanisms of action of the disease, or even the drug, will be the same in the mice as in the humans. Also, the mice have to be immunosuppressed to accept the graft, which could also be a drawback of the model.

Genetically engineered mouse models (GEMM) can be used to mimic a range of human diseases that are caused by genetic mutations, especially where mouse and human genes have direct counterparts (5), such as some cancers (8), though animal models

are less clear-cut for other diseases such as metabolic diseases.

“The best approach is to start with the human disease, find the mutations that are responsible, and then work these back into the animal model,” says Violette.

Genetically engineered mouse models can also be used to predict pharmacokinetics and pharmacodynamics (9).

Animal studies are also useful to work out the best route of administration—for example, if a drug can only be administered intravenously it is unlikely to be acceptable for daily use for a non-

“Most advances are based on a combination of academic and industry research, therefore it’s vital to collaborate with industry centers and pull it all into an actionable plan.”


“Animal models can only represent so much--sometimes studies in animals can kill a product that could have been effective, or allow through a product that’s ineffective or toxic in humans.”

CharloTTE KEywooD, ChiEf mEDiCal offiCEr aT aDDEx

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life threatening disorder. Animal studies are also useful to look at the interactions of combination therapeutics where it’s not ethical (or possible because of patent issues) to test these in humans (5).

“The issue with animal models is that they are not predictive and that [they] need to optimize the drugs to treat mice not humans!” says Helleday.

“Animal models are just one part—we can also use culture-based models and in silico models,” says Miller. “It’s an iterative process—the more you know, the better the model.”

tranSlational medicine approacheS—improving the modelingKnowing about the basic biology

can support the development of ex vivo and in silico modeling approaches to drug development, avoiding (or at least reducing) the reliance on animal models.

“These are all tools that have potential to optimize the process,” says Keywood, “and as the drugs that used them come to the clinic, this will validate the tools.”

ex vivo teSt platformSEx vivo test platforms use human tissue to test drug candidates for targeting, efficacy and toxicity. Access to human tissue samples, whether as perfused and isolated human organs (15) or as biobanks of human cryopreserved tissue, allows researchers to look at preclinical findings in human cells, which can validate or negate the

preclinical findings.

in Silico platformSIn silico platforms can assess the risks and benefits of new drugs virtually, without needing to synthesize large quantities of drugs or to develop animal models. This speeds up the process because large numbers of molecules can be screened at any one time. In silico platforms include pharmacokinetic, pharmacodynamic and toxicology modeling, drug-screening algorithms, toxicology databases and virtual animal models.

“The beauty of in silico tools and virtual screening is that they can be used at very early stages, for example using predictive toxicity modeling at the hit stage. This will allow a go/no go decision in early

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discovery on candidates that have a liability for toxicity,” says Dixon. “However, because some of these technologies are not proven, some companies spend more than they need by duplicating the screens using ‘real’ biology.”

taking the plunge—moving into patientSAt some point in the development process, once everything has been done to de-risk the process, drug developers have to move their clinical candidates into patients. To continue to reduce the risk and make go/no go decisions as clear as possible, there are a number of approaches that can support early clinical development, including using different styles of studies, and adapting existing styles of studies.

early clinical trialSVery early clinical trials can rely on patients with very advanced disease, who have no other treatment choices. However, explains Celniker, sometimes these include people whose disease is so serious that it cannot respond and it’s impossible to see efficacy, which can delay getting an answer.

“Solutions need to be aggregates of information about the disease with

prospective biomarkers and surrogate endpoints, along with animal models,” says Celniker. “It’s not always possible to check all

the boxes—it’s an art as well as a science.”

co-clinical trialSCo-clinical trials combine animal studies with human Phase I/II clinical studies, with the two mirroring and supporting each other. The animal studies can be used to identify predictive biomarkers, which are then validated in human tissue from the clinical trials. Biological findings can be correlated with outcomes such as the development of drug resistance. Findings from the preclinical studies can also be built

into adaptations of the clinical trial design, analysis and prediction, speeding up clinical development (8; 9; 10).

“Co-clinical trials and phase zero trials [see ‘Exploratory IND studies’] can be useful for answering specific questions in drug development,” says Miller.

adaptive deSigned clinical trialSAdaptive designed clinical trials allow researchers to modify one or more aspects of the trial as data are analyzed and at preplanned time points. This potentially allows earlier go/no go decisions, and reduces the number of clinical trial subjects who are treated with drugs at too low or too high doses, or with compounds that simply don’t work (1).

“Clinical trials are run under very strict protocols—if the Phase I and Phase IIa studies had a small amountofflexibilitybuiltinthenphysicians could fine-tune the studies based on patient responses, clinical observation and anecdotal findings, making it into an iterative process” says Helleday. “There is some level of risk here and while many patients are willing to take risks if it could lead to a treatment,

and regulatory bodies are changing their outlook, pharmaceutical companies are traditionally very risk-averse.”

There are practical issues associated with this type of trial—the patient population can shift, affecting the data that is collected and its ability to answer the trial questions (1).

exploratory ind StudieSMany drugs fail at Phase I because their pharmacokinetics, based on animal studies leading to selection of what is believed to be the optimum dose, are not good enough. This leads to the waste of a lot of time and money—fewer than 10% of the new medical entities (NMEs) actually make it to submission of approval for marketing (1; 8).

The FDA has created guidance

for companies wanting to use exploratory IND studies (eINDs, also known as Phase 0 trials). These are short microdosing trials that are carried out before Phase I trials in small groups of people (usually less than 30) and provide information from non-pharmacologic doses that are less than a hundredth of the expected dose. These studies do not involve dose escalation and could allow assessment of more than one clinical candidate, leading to selection of the most robust candidate, and go/no go decisions. Exploratory INDs are also more affordable for small biopharma companies (1; 8).

Information from eINDs includes (1; 8):•confirmationonthedrug’s

mechanism of action•drugpharmacokinetics,

pharmacodynamics and

“Solutions need to be aggregates of information about the disease with prospective biomarkers and surrogate endpoints, along with animal models.”

aBBiE CElniKEr, CEo of ElEVEn BioThErapEuTiCS.

“Co-clinical trials and phase zero trials [see ‘Exploratory IND studies’] can be useful for answering specific questions in drug development.”


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metabolism•drugtargeting•biodistribution.By supporting an early go/

no go decision, this type of trial could reduce the number of people exposed to ineffective or even potentially harmful drugs, improving the ethics of drug development as well as cutting the costs (5).

Collaborations between scientists and physicians support the iterative process of drug development, where what is learned from the first round of clinical candidates in Phase 0 trials feeds into the development of newer compounds. However, eINDs don’t provide all the answers—the studies and the doses are small, so may throw up false positives and false negatives, and some drugs will

have different pharmacokinetics and pharmacodynamics at low and higher dose levels (1).

“Exploratory IND studies or Phase 0 trials, which use microdosing to explore pharmacokinetics, could help determine the correct dose,” says Celniker, “but these don’t usually provide any biological readout. So in order to ask questions about efficacy in humans, you still need to carry out expensive safety testing in animals, and the cost of these can be equivalent to clinical trials. Rather than increasing the numbers of animals needed to predict efficacy, should we perhaps focus on improving the relevance of safety studies and the safety of the drugs, which will reduce the risk taken and the cost of the studies?”

WindoW-of- opportunity StudieSWindow of opportunity trials allow drug developers to test new medical entities in patients before they undergo standard treatment, such as surgery (9).

other approacheS to cutting attrition in drug developmentOther approaches to cutting attrition include making changes to existing drugs with a known safety profile, such as drug repurposing (developing a drug for a new indication); improving formulations, for example, making an oral or transdermal version of an intravenous or injectable drug; or creating a targeted form of a drug to reduce side effects and improve efficacy. l

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3. The productivity crisis in pharmaceutical R&D. pammolli, f, magazzini, l and riccaboni, m. Jun 2011, Nat Rev Drug Discov, Vol. 10, pp. 428-438.

4. Translational research. lean, m E, et al. 2008, BMJ, Vol. 337.

5. Improving the outcomes: developing cancer therapeutics. utku, n. Jan 2012, Future Oncol, Vol. 8, pp. 87-103.

6. fDa. FDA’s Critical Path Initiative. FDA. [Online] [Cited: 29 September 2012.] http://www.fda.gov/ScienceResearch/SpecialTopics/CriticalPathInitiative/ucm076689.htm.

7. Driving earlier clinical attrition: if you want to find the needle, burn down the haystack. Considerations for biomarker development. peck, r w. Apr 2007, Drug Discov Today, Vol. 12, pp. 289-294.

8. hollmer, mark. Avatar mice up ante for personalized drug treatment research. FierceBiotechResearch. [Online] 27 September 2012. [Cited: 30 September 2012.] http://www.fiercebiotechresearch.com/story/avatar-mice-ante-personalized-drug-treatment-research/2012-09-27.

9. pollack, andrew. Seeking Cures, Patients Enlist Mice Stand-Ins. New York Times. 25 September 2012.

10. Genetically engineered mouse models: closing the gap between preclinical data and trial outcomes. Singh, m, murriel, C l and Johnson, l. Jun 2012, Cancer Res, Vol. 72, pp. 2695-2700.

11. Genetically Engineered Cancer Models, But Not Xenografts, Faithfully Predict Anticancer Drug Exposure in Melanoma Tumors. Combest, austin J, et al. 9, 19 September 2012, The Oncologist, Vol. 17.

12. Ex Vivo Metrics, a preclinical tool in new drug development. Curtis, C g, Bilyard, K and Stephenson, h. 2008, J Transl Med, Vol. 6, pp. 5-5.

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