Upinder S. Bhalla, Ph.D.
Professor & Dean, NCBS, Bengaluru, India
Watching the network change during the formation of associative memory
The process of learning is measured through behavioural changes, but it is of enormous interest to understand its cellular and network basis. We used 2-photon imaging of hippocampal CA1 pyramidal neuron activity in mice to monitor such changes during the acquisition of a trace conditioning task. One of the questions in such learning is how the network retains a trace of a brief conditioned stimulus (a sound), until the arrival of a delayed unconditioned stimulus (a puff of air to the eye). During learning, the mice learn to blink when the tone is presented, well before the arrival of the air puff.
The mice learnt this task in 20-50 trials. We observed that in this time-frame the cells in the network changed the time of their peak activity, such that their firing times tiled the interval between sound and air puff. Thus the cells seem to form a relay of activity. We also observed an evolution in functional connectivity in the network, as measured by groupings of correlated cells. These groupings were stable till the learning protocol commenced, and then changed. Thus we have been able to observe two aspects of network learning: changes in activity (relay firing), and changes in connectivity (correlation groups).
Pradip K. Bhatnagar, Ph.D.
Former President & Head, Daiichi Sankyo Life Science Research Centre, India
Strategies for Diseases/Target Selection for Drug Discovery and a Multi-Targeted Approach to Metabolic Disorder
Drug discovery and development is a high risk and expensive undertaking. Although, technologies, such as, bioinformatics, genomics, high throughput screening and computer-aided design have helped identify targets, biomarkers, lead candidates and reduced the time required for advancing an idea from bench to clinic, but it still takes 10-12 years and costs approximately one billion dollars to bring a drug to market globally. Therefore, it is imperative that the strategies to reduce the risk and increase efficiency are carefully selected. In this presentation I would discuss strategies for selecting potential diseases, targets and provide an example of multi-targeted approach to metabolic disorder.
Colin Barrow, Ph.D.
Chair in Biotechnology, School of Life & Environmental Sciences, Deakin University, Australia
Nano-biotechnology: Omega-3 Oils and Nanofibres
The health benefits of long-chain omega-3 fatty acids are well established, especially for eicosapentaenoic acid (EPA) and docosapentaenoic acid (DHA) from fish and microbial sources. In fact, a billion dollar market exists for these compounds as nutritional supplements, functional foods and pharmaceuticals. This presentation will describe some aspects of our omega-3 biotechnology research that are at the intersection of Nano-biotechnology and oil chemistry. These include the use of lipases for the concentration of omega-3 fats, through immobilization of these lipases on nanoparticles, and the microencapsulation and stabilization of omega-3 oils for functional foods. I will also describe some of our work on the enzymatic production of resolvins using lipoxygenases, and the fermentation of omega-3 oils from marine micro-organisms. Finally, I will describe some of our work on the formation of amyloid fibrils and graphene for various applications in nano-biotechnology.
Shantikumar Nair, Ph.D.
Professor & Director, Amrita Center for Nanosciences & Molecular Medicine, Amrita University, India
Spatially Distributed and Hierarchical Nanomaterials in Biotechnology
Although nano materials are well investigated in biotechnology in their zero-, one- and two-dimensional forms, three-dimensional nanomaterials are relatively less investigated for their biological applications. Three dimensional nano materials are much more complex with several structural and hierarchical variables controlling their mechanical, chemical and biological functionality. In this talk examples are given of some complex three dimensional systems including, scaffolds, aggregates, fabrics and membranes. Essentially three types of hierarchies are considered: one-dimensional hierarchy, two-dimensional hierarchy and three-dimensional hierarchy each giving rise to unique behaviors.
Nader Pourmand, Ph.D.
Director, UCSC Genome Technology Center,University of California, Santa Cruz
Biosensor and Single Cell Manipulation using Nanopipettes
Approaching sub-cellular biological problems from an engineering perspective begs for the incorporation of electronic readouts. With their high sensitivity and low invasiveness, nanotechnology-based tools hold great promise for biochemical sensing and single-cell manipulation. During my talk I will discuss the incorporation of electrical measurements into nanopipette technology and present results showing the rapid and reversible response of these subcellular sensors to different analytes such as antigens, ions and carbohydrates. In addition, I will present the development of a single-cell manipulation platform that uses a nanopipette in a scanning ion-conductive microscopy technique. We use this newly developed technology to position the nanopipette with nanoscale precision, and to inject and/or aspirate a minute amount of material to and from individual cells or organelle without comprising cell viability. Furthermore, if time permits, I will show our strategy for a new, single-cell DNA/ RNA sequencing technology that will potentially use nanopipette technology to analyze the minute amount of aspirated cellular material.
Kal Ramnarayan, Ph.D.
Co-founder President & Chief Scientific Officer, Sapient Discovery, San Diego, CA, USA
A cost-effective approach to Protein Structure-guided Drug Discovery: Aided by Bioinformatics, Chemoinformatics and computational chemistry
With the mapping of the human genome completed almost a decade ago, efforts are still underway to understand the gene products (i.e., proteins) in the human biological and disease pathways. Deciphering such information is very important for the discovery and development of small molecule drugs as well as protein therapeutics for various human diseases for which no cure exists. As an example, with more than 500 members, the kinase family of protein targets continues to be an important and attractive class for drug discovery. While how many of the members in this family are actually druggable is still to be established, there are several ongoing efforts on this class of proteins across a broad spectrum of disease categories. Even though in general the protein structural topology might looks similar, there are issues with respect selectivity of identified small molecule inhibitors when, the lead molecule discovery is carried out at the ATP binding site. As an added complexity, allosteric modulators are needed for some of the members, but the actual site for such modulation on the protein target can not resolved with uncertainty. In this presentation we will describe a bioinformatics and computational based platform for small molecule discovery for protein targets that are involved in protein-protein interactions as well as targets like kinases and phosphatases. We will describe a computational approach in which we have used an informatics based platform with several hundred kinases to sort through in silico and identify inhibitors that are likely to be highly selective in the lead generation phase. We will discuss the implication of this approach on the drug discovery of the kinase and phosphatase classes in general and independent of the disease category.
Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
Satheesh Babu T. G., Ph.D.
Associate Professor, Department of Sciences, School of Engineering, Amrita University, Coimbatore, India
Nanomaterials for ‘enzyme-free’ biosensing
Enzyme based sensors have many draw backs such as poor storage stability, easily affected by the change in pH and temperature and involves complicated enzyme immobilization procedures. To address this limitation, an alternative approach without the use of enzyme, “non-enzymatic” has been tried recently. Choosing the right catalyst for direct electrochemical oxidation / reduction of a target molecule is the key step in the fabrication of non-enzymatic sensors.
Non-enzymatic sensors for glucose, creatinine, vitamins and cholesterol are fabricated using different nanomaterials, such as nanotubes, nanowires and nanoparticles of copper oxide, titanium dioxide, tantalum oxide, platinum, gold and graphenes. These sensors selectively catalyse the targeted analyte with very high sensitivity. These nanomaterials based sensors combat the drawbacks of enzymatic sensors.
The global healthcare scene of which the pharmaceutical industry and its products are integral components is today at the cross roads. The high and unaffordable costs of drug research with estimates of over 1 billion dollars for every new drug discovered and developed, the very low success rates, the high degree of obsolescence due to undesirable adverse drug reactions, the decline in the development pipeline of new drugs, patent expiries leading to generic competition and the public’s disillusionment with use of chemicals for human consumption as drugs have all significantly contributed to the problems of this lifeline industry. The strategy adopted by the large R&D based Corporations to get bigger and bigger through mergers and acquisitions to improve cost-effectiveness and productivity of R&D has so far not worked effectively. Consequently, one of the recent trends in healthcare, articulated by many experts is to look for alternate or even complementary approaches to reduce the impact of rising costs of drugs on healthcare. Various new strategies for drug discovery such as the use of Natural Products especially medicinal plants are being actively pursued by healthcare planners and providers. Side by side, traditional systems of medicine whether from the oriental countries or the western nations are also having a serious relook to understand their usefulness in healthcare. To achieve its legitimate position in the healthcare scenario, it is essential to scientifically validate their claimed utility through appropriate and systematic research efforts including pre-clinical and clinical studies. In addition to their own use as medicines, knowledge on the Indian Traditional Medicines can be used as a platform for new drug discovery. The huge potential for carrying out systematic R&D programs for new Drug Discovery based on natural products and possible strategies to realise them in the coming decades will be explained in this presentation.
Ramani A. Aiyer, Ph.D., MBA
Principal, Shasta BioVentures, San Jose, CA, USA
New Drug R&D in India: Challenges & Opportunities
New drug discovery and development has become a global endeavor, with Western big pharmaceutical companies farming out more and more chemistry and biology research to Asia, particularly India and China. During the last decade, several Indian pharmaceutical companies have embarked on ambitious R&D programs, with slow but steady progress in developing new chemical / molecular entities. The Indian government has also made a strong commitment to promote innovation and entrepreneurship in the biotechnology sector. The first part of the talk will focus on a case study showing the entire process of discovery and development of a new drug recently launched for Rheumatoid Arthritis. We will then address the challenges of conducting innovative R&D in India and actions necessary to overcome them. The second part of the talk will make the case for developing Ayurvedic drug formulations for the Western / Global markets, again using the example of Rheumatoid Arthritis (Aamavaata). Ayurveda takes a holistic approach to disease diagnosis and therapy based on interactions among body type (prakriti), tri-doshas (three body humors), sapta-dhatus (seven tissues) and malas (excretions). The drugs prescribed are usually herbo-mineral formulations comprising multiple medicinal plants and / or metals. The manufacturing processes date back to Ayurvedic texts several thousand years old, and are compiled in the Ayurvedic Pharmacopeia. Also, the treatment modalities and drug formulations are “personalized” to fit different patient types, based on the holistic diagnoses mentioned earlier. There is a tremendous need to establish a sound basis for Ayurvedic drug discovery R&D for the modern world. We must find a scientific and ethical way to leverage the vast body of anecdotal and possibly retrospective data on patients undergoing Ayurvedic treatment. Combined with in vitro and in vivo biological data on Ayurvedic herbo-mineral formulations, the adoption of stringent manufacturing practices, and designing sound clinical trials to establish the safety and efficacy, India has a golden opportunity to expand the reach of Ayurvedic drugs into Western / Global medical practice.