Jaydeep Unni, Ph.D.
Sr. Project Manager, Robert Bosch Healthcare Systems, Palo Alto, CA
Remote Patient Monitoring – Challenges and Opportunities
Remote Patient Monitoring (RPM) is gaining importance and acceptance with rising number of chronic disease conditions and with increase in the aging population. As instances of Heart diseases, Diabetes etc are increasing the demand for these technologies are increasing. RPM devices typically collect patient vital sign data and in some case also patient responses to health related questions. Thus collected data is then transmitted through various modalities (wireless/Bluetooth/cellular) to Hospitals/Doctor’s office for clinical evaluation. With these solutions Doctors are able to access patient’s vital data ‘any time any where’ thus enabling them to intervene on a timely and effective manner. For older adult population chronic disease management, post-acute care management and safety monitoring are areas were RPM finds application. That said, there are significant challenges in adoption of Remote Patient Monitoring including patient willingness and compliance for adoption, affordability, availability of simpler/smarter technology to mention a few. But experts contend that if implemented correctly Remote Patient Monitoring can contain healthcare expenditure by reducing avoidable hospitalization while greatly improving quality of care.
Seeram Ramakrishna, Ph.D.
Director, Center for Nanofibers & Nanotechnology, National University of Singapore
Biomaterials: Future Perspectives
From the perspective of thousands of years of history, the role of biomaterials in healthcare and wellbeing of humans is at best accidental. However, since 1970s with the introduction of national regulatory frameworks for medical devices, the biomaterials field evolved and reinforced with strong science and engineering understandings. The biomaterials field also flourished on the backdrop of growing need for better medical devices and medical treatments, and sustained investments in research and development. It is estimated that the world market size for medical devices is ~300 billion dollars and for biomaterials it is ~30 billion dollars. Healthcare is now one of the fastest growing sectors worldwide. Legions of scientists, engineers, and clinicians worldwide are attempting to design and develop newer medical treatments involving tissue engineering, regenerative medicine, nanotech enabled drug delivery, and stem cells. They are also engineering ex-vivo tissues and disease models to evaluate therapeutic drugs, biomolecules, and medical treatments. Engineered nanoparticles and nanofiber scaffolds have emerged as important class of biomaterials as many see them as necessary in creating suitable biomimetic micro-environment for engineering and regeneration of various tissues, expansion & differentiation of stem cells, site specific controlled delivery of biomolecules & drugs, and faster & accurate diagnostics. This lecture will capture the progress made thus far in pre-clinical and clinical studies. Further this lecture will discuss the way forward for translation of bench side research into the bed side practice. This lecture also seeks to identify newer opportunities for biomaterials beyond the medical devices.
Manzoor K, Ph.D.
Professor, Centre for Nanoscience & Molecular Medicine, Amrita University
Targeting aberrant cancer kinome using rationally designed nano-polypharmaceutics
Manzoor Koyakutty, Archana Ratnakumary, Parwathy Chandran, Anusha Ashokan, and Shanti Nair
`War on Cancer’ was declared nearly 40 years ago. Since then, we made significant progress on fundamental understanding of cancer and developed novel therapeutics to deal with the most complex disease human race ever faced with. However, even today, cancer remains to be the unconquered `emperor of all maladies’. It is well accepted that meaningful progress in the fight against cancer is possible only with in-depth understanding on the molecular mechanisms that drives its swift and dynamic progression. During the last decade, emerging new technologies such as nanomedicine could offer refreshing life to the `war on cancer’ by way of providing novel methods for molecular diagnosis and therapy.
In the present talk, we discuss our approaches to target critically aberrant cancer kinases using rationally designed polymer-protein and protein-protein core-shell nanomedicines. We have used both genomic and proteomic approaches to identify many intimately cross-linked and complex aberrant protein kinases behind the drug resistance and uncontrolled proliferation of refractory leukemic cells derived from patients. Small molecule inhibitors targeted against oncogenic pathways in these cells were found ineffective due to the involvement of alternative survival pathways. This demands simultaneous inhibition more than one oncogenic kinases using poly-pharmaceutics approach. For this, we have rationally designed core-shell nanomedicines that can deliver several small molecules together for targeting multiple cancer signalling. We have also used combination of small molecules and siRNA for combined gene silencing together with protein kinase inhibition in refractory cancer cells. Optimized nanomedicines were successfully tested in patient samples and found enhanced cytotoxicity and molecular specificity in drug resistant cases.
Nano-polypharmaceutics represents a new generation of nanomedicines that can tackle multiple cancer mechanisms simultaneously. Considering the complexity of the disease, such therapeutic approaches are not simply an advantage, but indispensable.
Acknowledgements:
We thank Dept. of Biotechnology and Dept. Of Science and Technology,Govt. of India for the financial support through `Thematic unit of Excellence in Medical NanoBiotechnology’ and `Nanomedicine- RNAi programs’.
Srisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA
Applying Machine learning for Automated Identification of Patient Cohorts
Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland
Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.
Pandiaraj Manickam, Niroj Kumar Sethy, Kalpana Bhargava, Vepa Kameswararao and Karunakaran Chandran
Designing electrochemical label free immunosensors for cytochrome c using nanocomposites functionalized screen printed electrodes
Release of cytochrome c (cyt c) from mitochondria into cytosol is a hallmark of apoptosis, used as a biomarker of mitochondrial dependent pathway of cell death (Kluck et al. 1997; Green et al. 1998). We have previously reported cytochrome c reductase (CcR) based biosensors for the measurement of mitochondrial cyt c release (Pandiaraj et al. 2013). Here, we describe the development of novel label-free, immunosensor for cyt c utilizing its specific monoclonal antibody. Two types of nanocomposite modified immunosensing platforms were used for the immobilization of anti-cyt c; (i) Self-assembled monolayer (SAM) functionalized gold nanoparticles (GNP) in conducting polypyrrole (PPy) modified screen printed electrodes (SPE) (ii) Carbon nanotubes (CNT) incorporated PPy on SPE. The nanotopologies of the modified electrodes were confirmed by scanning electron microscopy (SEM). Cyclic voltammetry, electrochemical impedance spectroscopy (EIS) were used for probing the electrochemical properties of the nanocomposite modified electrodes. Method for cyt c quantification is based on the direct electron transfer between Fe3+/Fe2+-heme of cyt c selectively bound to anti-cyt c modified electrode. The Faradaic current response of these nanoimmunosensor increases with increase in cyt c concentration. The procedure for cyt c detection was also optimized (pH, incubation times, and characteristics of electrodes) to improve the analytical characteristics of immunosensors. The analytical performance of anti-cyt c biofunctionalized GNP-PPy nanocomposite platform (detection limit 0.5 nM; linear range: 0.5 nM–2 μM) was better than the CNT-PPy (detection limit 2 nM; linear range: 2 nM-500nM). The detection limits were well below the normal physiological concentration range (Karunakaran et al. 2008). The proposed method does not require any signal amplification or labeled secondary antibodies contrast to widespread ELISA and Western blot. The immunosensors results in simple and rapid measurement of cyt c and has great potential to become an inexpensive and portable device for conventional clinical immunoassays.