The pipeline and future of drug development in schizophrenia

While the current antipsychotic medications have profoundly impacted the treatment of schizophrenia over the past 50 years, the newer atypical antipsychotics have not fulfilled initial expectations, and enormous challenges remain in long-term treatment of this debilitating disease. In particular, improved treatment of the negative symptoms and cognitive dysfunction in schizophrenia which greatly impact overall morbidity is needed. In this review we will briefly discuss the current pipeline of drugs for schizophrenia, outlining many of the strategies and targets currently under investigation for the development of new schizophrenia drugs. Many of these compounds have great potential as augmenting agents in the treatment of negative symptoms and cognition. In addition, we will highlight the importance of developing new paradigms for drug discovery in schizophrenia and call for an increased role of academic scientists in discovering and validating novel drug targets. Indeed, recent breakthroughs in genetic studies of schizophrenia are allowing for the development of hypothesis-driven approaches for discovering possible disease-modifying drugs for schizophrenia. Thus, this is an exciting and pivotal time for the development of truly novel approaches to drug development and treatment of complex disorders like schizophrenia

Impaired associative learning in schizophrenia: behavioral and computational studies

Associative learning is a central building block of human cognition and in large part depends on mechanisms of synaptic plasticity, memory capacity and fronto–hippocampal interactions. A disorder like schizophrenia is thought to be characterized by altered plasticity, and impaired frontal and hippocampal function. Understanding the expression of this dysfunction through appropriate experimental studies, and understanding the processes that may give rise to impaired behavior through biologically plausible computational models will help clarify the nature of these deficits. We present a preliminary computational model designed to capture learning dynamics in healthy control and schizophrenia subjects. Experimental data was collected on a spatial-object paired-associate learning task. The task evinces classic patterns of negatively accelerated learning in both healthy control subjects and patients, with patients demonstrating lower rates of learning than controls. Our rudimentary computational model of the task was based on biologically plausible assumptions, including the separation of dorsal/spatial and ventral/object visual streams, implementation of rules of learning, the explicit parameterization of learning rates (a plausible surrogate for synaptic plasticity), and learning capacity (a plausible surrogate for memory capacity). Reductions in learning dynamics in schizophrenia were well-modeled by reductions in learning rate and learning capacity. The synergy between experimental research and a detailed computational model of performance provides a framework within which to infer plausible biological bases of impaired learning dynamics in schizophrenia

Overview on cell-biomaterial interactions

Biomaterials, a name given to express materials used as medical implants, indwelling devices, extracorporeal ones and other categories in several medical fields, have increasingly played a significant role when aiming at improving the quality of life in humans. The behavior of a biomaterial with the surrounding physiologic environment is of major relevance for determining the in vivo performance and host acceptance of any device. Indeed, the biocompatibility and bio-functionality of implantable devices remains a serious challenge in establishing the devices function and lifetime. Several research efforts have been conducted to further understand and control the interactions between biomaterials and cell-mediated processes, aiming at the definition of the main guidelines that regulate materials biocompatibility. Several criteria should be met when considering a biomaterial for a specific application. On the materials perspective, its composition, mechanical, physicochemical, thermal, electrical properties must be well understood. In parallel, knowledge on the cell-biomaterial interaction mechanisms (including specific adhesion proteins and cell receptors, signal transduction, cell differentiation, tissue development, host immune response mechanisms, to name a few processes) must be attained, to better characterize, follow up and control cell-biomaterial interactions. This review attempts to define the basic phenomenon that take place when a biomaterial comes into contact with host living tissues. Numerous strategies have been investigated to overcome body reactions induced by the implantation of devices. These strategies, their advantages and limitations, along with the fundamentals underlying biomaterials-tissue interactions and current research on biomaterial surface modification are discussed. Besides, the use of polymeric biomaterials for use in age-related macular degeneration will be presented as a case study