Systems-Based Discovery Advances Drug Development

New approaches for developing multi-targeted drug combinations for disease modification of complex brain disorders. Does epilepsy prevention become a realistic goal?

Over decades, the prevailing standard in drug discovery was the concept of designing highly selective compounds that act on individual drug targets. However, more recently, multi-target and combinatorial drug therapies have become an important treatment modality in complex diseases, including neurodegenerative diseases such as Alzheimer's and Parkinson's disease. The development of such network-based approaches is facilitated by the significant advance in our understanding of the pathophysiological processes in these and other complex brain diseases and the adoption of modern computational approaches in drug discovery and repurposing. However, although drug combination therapy has become an effective means for the symptomatic treatment of many complex diseases, the holy grail of identifying clinically effective disease-modifying treatments for neurodegenerative and other brain diseases remains elusive. Thus, despite extensive research, there remains an urgent need for novel treatments that will modify the progression of the disease or prevent its development in patients at risk. Here we discuss recent approaches with a focus on multi-targeted drug combinations for prevention or modification of epilepsy. Over the last ~10 years, several novel promising multi-targeted therapeutic approaches have been identified in animal models. We envision that synergistic combinations of repurposed drugs as presented in this review will be demonstrated to prevent epilepsy in patients at risk within the next 5-10 years.

Network pharmacology for antiepileptogenesis: Tolerability and neuroprotective effects of novel multitargeted combination treatments in nonepileptic vs. post-status epilepticus mice

Network-based approaches in drug discovery comprise both development of novel drugs interacting with multiple targets and repositioning of drugs with known targets to form novel drug combinations that interact with cellular or molecular networks whose function is disturbed in a disease. Epilepsy is a complex network phenomenon that, as yet, cannot be prevented or cured. We recently proposed multitargeted, network-based approaches to prevent epileptogenesis by combinations of clinically available drugs chosen to impact diverse epileptogenic processes. In order to test this strategy preclinically, we developed a multiphase sequential study design for evaluating such drug combinations in rodents, derived from human clinical drug development phases. Because pharmacokinetics of such drugs are known, only the tolerability of novel drug combinations needs to be evaluated in Phase I in öhealthy" controls. In Phase IIa, tolerability is assessed following an epileptogenic brain insult, followed by antiepileptogenic efficacy testing in Phase IIb. Here, we report Phase I and Phase IIa evaluation of 7 new drug combinations in mice, using 10 drugs (levetiracetam, topiramate, gabapentin, deferoxamine, fingolimod, ceftriaxone, α-tocopherol, melatonin, celecoxib, atorvastatin) with diverse mechanisms thought to be important in epileptogenesis. Six of the 7 drug combinations were well tolerated in mice during prolonged treatment at the selected doses in both controls and during the latent phase following status epilepticus induced by intrahippocampal kainate. However, none of the combinations prevented hippocampal damage in response to kainate, most likely because treatment started only 16-18 h after kainate. This suggests that antiepileptogenic or disease-modifying treatment may need to start earlier after the brain insult. The present data provide a rich collection of tolerable, network-based combinatorial therapies as a basis for antiepileptogenic or disease-modifying efficacy testing.

Managing the innovation supply chain to maximize personalized medicine

Personalized medicine epitomizes an evolving model of care tailored to the individual patient. This emerging paradigm harnesses radical technological advances to define each patient's molecular characteristics and decipher his or her unique pathophysiological processes. Translated into individualized algorithms, personalized medicine aims to predict, prevent, and cure disease without producing therapeutic adverse events. Although the transformative power of personalized medicine is generally recognized by physicians, patients, and payers, the complexity of translating discoveries into new modalities that transform health care is less appreciated. We often consider the flow of innovation and technology along a continuum of discovery, development, regulation, and application bridging the bench with the bedside. However, this process also can be viewed through a complementary prism, as a necessary supply chain of services and providers, each making essential contributions to the development of the final product to maximize value to consumers. Considering personalized medicine in this context of supply chain management highlights essential points of vulnerability and/or scalability that can ultimately constrain translation of the biological revolution or potentiate it into individualized diagnostics and therapeutics for optimized value creation and delivery.

Using genetic findings in autism for the development of new pharmaceutical compounds

RATIONALE

The main reason for the current lack of effective treatments for the core symptoms of autism is our limited understanding of the biological mechanisms underlying this heterogeneous group of disorders. A primary value of genetic research is enhancing our insight into the biology of autism through the study of identified autism risk genes.

OBJECTIVES

In the current review we discuss (1) the genes and loci that are associated with autism, (2) how these provide us with essential cues as to what neurobiological mechanisms may be involved, and (3) how these mechanisms may be used as targets for novel treatments. Next, we provide an overview of currently ongoing clinical trials registered at clinicaltrials.gov with a variety of compounds. Finally, we review current approaches used to translate knowledge derived from gene discovery into novel pharmaceutical compounds and discuss their pitfalls and problems.

CONCLUSIONS

An increasing number of genetic variants associated with autism have been identified. This will generate new ideas about the biological mechanisms involved in autism, which in turn may provide new leads for the development of novel pharmaceutical compounds. To optimize this pipeline of drug discovery, large-scale international collaborations are needed for gene discovery, functional validation of risk genes, and improvement of clinical outcome measures and clinical trial methodology in autism.

Molecular insights provide the critical path to disease mitigation

The revolution in scientific innovation, driven by the engines of enabling technologies, is increasingly capable of deconstructing complex disease processes for the express purpose of reconstructing patient-specific solutions. These revelations in biological mechanisms provide the pressure points of opportunity for radical discovery and development to advance modern health care. Principles of mechanism-based discovery and their translation into therapeutic algorithms will, however, be challenged in the near term by emerging global public health crises that currently have no immediate solutions: chronic diseases, obesity, antibiotic-resistant infections, dementia, depression. The threat of these pandemics (multiplied in an increasingly aging population), the global burden of disease they represent, and their worldwide assault on human capital underscore the importance of continued and accelerated investments in science-propelled practice advancement, converting new knowledge into delivery of tangible health solutions. In that context, this annual issue of CPT on therapeutics innovations highlights remarkable recent successes in the discovery-development paradigm translating molecular innovations into diagnostic and therapeutic realities that transform the management of disease, impacting global health.

The innovative medicines initiative: a public private partnership model to foster drug discovery

The Innovative Medicines Initiative (IMI) is a large-scale public–private partnership between the European Commission and the European Federation of Pharmaceutical Industries and Associations (EFPIA). IMI aims to boost the development of new medicines across Europe by implementing new collaborative endeavours between large pharmaceutical companies and other key actors in the health-care ecosystem, i.e., academic institutions, small and medium enterprises, patients, and regulatory authorities. Currently there are more than 40 IMI projects covering the whole value chain of pharmaceutical R&D, but with a strong focus on drug discovery, as an ideal arena where the PPP concept of pre-competitive collaboration can rapidly deliver results. This article review recent achievements of the IMI consortia of relevance to drug discovery, providing proof-of-concept evidence for the efficiency of this new model of collaboration.

Clinical relevance of target identity and biology: implications for drug discovery and development

Many of the most commonly used drugs precede techniques for target identification and drug specificity and were developed on the basis of efficacy and safety, an approach referred to as classical pharmacology and, more recently, phenotypic drug discovery. Although substantial gains have been made during the period of focus on target-based approaches, particularly in oncology, these approaches have suffered a high overall failure rate and lower productivity in terms of new drugs when compared with phenotypic approaches. This review considers the importance of target identity and biology in clinical practice from the prescriber's viewpoint. In evaluating influences on prescribing behavior, studies suggest that target identity and mechanism of action are not significant factors in drug choice. Rather, patients and providers consistently value efficacy, safety, and tolerability. Similarly, the Food and Drug Administration requires evidence of safety and efficacy for new drugs but does not require knowledge of drug target identity or target biology. Prescribers do favor drugs with novel mechanisms, but this preference is limited to diseases for which treatments are either not available or suboptimal. Thus, while understanding of drug target and target biology is important from a scientific perspective, it is not particularly important to prescribers, who prioritize efficacy and safety.