Successful drug delivery using implantable pumps may be found in over 12,500 published articles. Their versatility in delivering continuous infusion, intermittent or complex infusion protocols acutely or chronically has made them ubiquitous in drug discovery and basic research. The recent availability of iPRECIO®, a programmable, refillable, and implantable infusion pump has made it possible to carry out quantitative pharmacology (PKPD) in single animals. When combined with specialized catheters, specific administration sites have been selected. When combined with radiotelemetry, the physiologic gold standard, more sensitive and powerful means of detecting drug induced therapeutic, and/or adverse effects has been possible. Numerous application examples are cited from iPRECIO® use in Japan, United States, and Europe with iPRECIO® as an enabling drug delivery device where the refillable and programmability functionality were key benefits. The ability to start/stop drug delivery and to have control periods prior dosing made it possible to have equivalent effects at a much lower dose than previously studied. Five different iPRECIO® applications are described in detail with references to the original work where the implantable, refillable, and programmable benefits are demonstrated with their different end-points.

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Background Cardiovascular disease (CVD) is the leading cause of death world-wide. Existing tools for identification of CVD risk have modest predictive power and discrimination. New biomarkers for CVD prediction are urgently needed. Hypothesis We have used 1 H NMR metabonomic profiling of serum to identify novel biomarkers for incident CVD. Methods We investigated 9,179 men and women participating in the London Life Sciences Population study. Participants were recruited between 2002-2008 from the lists of 58 GPs in London UK, and assessed for baseline CVD risk factors, including smoking, body mass index, waist circumference, blood pressure, fasting glucose and lipid profile. Participants were followed for CVD mortality to July 2011 (mean 5.5 years per person). 1 H NMR metabonomic profiling was done on baseline serum sample by 12T Bruker spectrometer, with quantification of 44 fatty acid and low molecular weight markers. Results There were 161 CVD deaths. Compared to survivors, people with CVD death were older, had higher prevalence of type-2 diabetes and cigarette smoking, higher blood pressure, body mass index, glucose, and lower total and HDL cholesterol (Table). Framingham risk scores were higher in cases with CVD death than survivors (18.7±0.9% vs. 11.4±0.7%, P=10 -31 ). We found six NMR metabolites associated with incident CVD at P<0.05; odds ratios (95%CI) for CVD per 1SD increase in biomarker ranged from 1.19 (1.07-1.33, P=0.007) to 1.65 (1.44-1.89, P=3x10 -13 ). The associations of NMR metabolites with CVD were not materially changed by adjustment for age, gender and Framingham risk score. The AUC for prediction of incident CVD was 0.74 using Framingham risk score alone, and 0.77 with incorporation of metabonomic measures. Conclusions We identified six novel biomarkers for incident CVD; these are independent of known CVD risk factors and may improve CVD risk prediction. Our findings demonstrate the potential utility of metabonomic profiling for biomarker discovery and risk stratification. CVD deaths Survivors P Total no of people 161 9018 Age (years) 61.6 (0.5) 53.4 (0.4) 0.001 Male gender (%) 98.2 85.8 <0.001 Smoking (%) 73 49 <0.001 Diabetes (%) 49 20 <0.001 Systolic blood Pressure (mmHg) 144.7 (22.7) 134.0 (19.2) <0.001 Body mass index (kg/m 2 ) 28.4 (5.6) 27.3 (4.3) 0.002 Total cholesterol (mmol/L) 4.8 (1.2) 5.2 (1.1) <0.001 HDL cholesterol (mmol/L) 1.20 1.25 0.064 Glucose (mmol/L) 7.1 5.9 <0.001 Results provided as mean or %.

Background The genetic architecture and variation of Indian Asians, who represent one quarter of the world's population, has not been described. This represents an important obstacle to the identification of the genetic factors contributing to diseases encountered in Indian Asians. Aim To identify and describe the patterns of genetic variation in Indian Asians. Methods We carried out high-depth whole genome sequencing of 8 Indian Asian men, using paired-end and mate-pair libraries, and Illumina GAII x instruments. We used Stampy, with BWA as a pre-mapper, to align reads to Genome Reference Consortium build 37 of the human genome (GRCh37). We used GATK and SAMtools to call SNPs and indels; accepting genetic variants called by both algorithms as confirmed. Results Mean coverage was 28.4x (range 13.9 to 32.5x); 99.8% of the mappable genome was covered by at least one read in each sample. We found 6,602,840 autosomal SNPs (mean 3,318,386 per person) of which 436,823 (6.6%) are novel (not in dbSNP132 or 1000G June 2011). The majority of novel SNPs were singletons (88% vs 20% for known SNPs). There were 50,585 novel SNPs present at least twice (ie MAF>10%), and 2,174 novel SNPs predicted to affect protein coding. Amongst the novel cSNPs that are identified as pathogenic by SIFT or PolyPhen2, 145 are in genes linked by OMIM to human disease, including obesity ( FTO , UCP1 ), diabetes mellitus ( CDKAL1 , GCGR , HNF1B ), lipid metabolism ( APOB ), renal disease ( NPHP4, PKD1 ), hypertension ( NOS2 ), iron and B vitamin metabolism ( CUBN , TCN2, TF ), and susceptibility to malaria and leprosy ( CR1 , FCGR2A , NOS2, TLR1 ). There were 65,613 novel autosomal indels of which 35,097 are present at least twice, and 2,301 novel deletions >100bp. We found that amongst the novel SNPs and indels discovered, >50% are not in high LD (r 2 ≥0.8) with tagSNPs on available high-density microarrays Conclusions Our results reveal 502,436 new genetic variants amongst Indian Asians, including coding SNPs and indels in genes involved in atherosclerosis, carbohydrate and lipid metabolism, immunity and inflammation. The majority of novel variants are in low LD with standard commercial micro-arrays, indicating that these genome-wide arrays do not capture Indian Asian specific genetic variation. Our findings will inform the design of future studies to identify the genetic factors contributing to cardiovascular disease and other disorders that are more common amongst Indian Asians.

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