Bo Wang

IMPORTANCE: Many investigational drugs fail in late-stage clinical development. A better understanding of why investigational drugs fail can inform clinical practice, regulatory decisions, and future research. OBJECTIVE: To assess factors associated with regulatory approval or reasons for failure of investigational therapeutics in phase 3 or pivotal trials and rates of publication of trial results. DESIGN, SETTING, AND PARTICIPANTS: Using public sources and commercial databases, we identified investigational therapeutics that entered pivotal trials between 1998 and 2008, with follow-up through 2015. Agents were classified by therapeutic area, orphan designation status, fast track designation, novelty of biological pathway, company size, and as a pharmacologic or biologic product. MAIN OUTCOMES AND MEASURES: For each product, we identified reasons for failure (efficacy, safety, commercial) and assessed the rates of publication of trial results. We used multivariable logistic regression models to evaluate factors associated with regulatory approval. RESULTS: Among 640 novel therapeutics, 344 (54%) failed in clinical development, 230 (36%) were approved by the US Food and Drug Administration (FDA), and 66 (10%) were approved in other countries but not by the FDA. Most products failed due to inadequate efficacy (n = 195; 57%), while 59 (17%) failed because of safety concerns and 74 (22%) failed due to commercial reasons. The pivotal trial results were published in peer-reviewed journals for 138 of the 344 (40%) failed agents. Of 74 trials for agents that failed for commercial reasons, only 6 (8.1%) were published. In analyses adjusted for therapeutic area, agent type, firm size, orphan designation, fast-track status, trial year, and novelty of biological pathway, orphan-designated drugs were significantly more likely than nonorphan drugs to be approved (46% vs 34%; adjusted odds ratio [aOR], 2.3; 95% CI, 1.4-3.7). Cancer drugs (27% vs 39%; aOR, 0.5; 95% CI, 0.3-0.9) and agents sponsored by small and medium-size companies (28% vs 42%; aOR, 0.4; 95% CI, 0.3-0.7) were significantly less likely to be approved. CONCLUSIONS AND RELEVANCE: Roughly half of investigational drugs entering late-stage clinical development fail during or after pivotal clinical trials, primarily because of concerns about safety, efficacy, or both. Results for the majority of studies of investigational drugs that fail are not published in peer-reviewed journals.

Partial atomic charges are widely used for the description of charge distributions of molecules and solids. These charges are useful to indicate the extent of charge transfer and charge flow during chemical reactions in batteries, fuel cells, and catalysts and to characterize charge distributions in capacitors, liquid-phase electrolytes, and solids and at electrochemical interfaces. However, partial atomic charges given by various charge models differ significantly, especially for systems containing metal atoms. In the present study, we have compared various charge models on both molecular systems and extended systems, including Hirshfeld, CM5, MK, ChElPG, Mulliken, MBS, NPA, DDEC, LoProp, and Bader charges. Their merits and drawbacks are compared. The CM5 charge model is found to perform well on the molecular systems, with a mean unsigned percentage deviation of only 9% for the dipole moments. We therefore formulated it for extended systems and applied it to study charge flow during the delithiation process in lithium-containing oxides used as cathodes. Our calculations show that the charges given by the CM5 charge model are reasonable and that during the delithiation process, the charge flow can occur not only on the transition metal but also on the anions. The oxygen atoms can lose a significant density of electrons, especially for deeply delithiated materials. We also discuss other methods in current use to analyze the charge transfer and charge flow in batteries, in particular the use of formal charge, spin density, and orbital occupancy. We conclude that CM5 charges provide useful information in describing charge distributions in various materials and are very promising for the study of charge transfer and charge flows in both molecules and solids.

Postharvest kiwifruit continues to ripen for a period until it reaches the optimal "eating ripe" stage. Without damaging the fruit, it is very difficult to identify the ripeness of postharvest kiwifruit by conventional means. In this study, an electronic nose (E-nose) with 10 metal oxide semiconductor (MOS) gas sensors was used to predict the ripeness of postharvest kiwifruit. Three different feature extraction methods (the max/min values, the difference values and the 70th s values) were employed to discriminate kiwifruit at different ripening times by linear discriminant analysis (LDA), and results showed that the 70th s values method had the best performance in discriminating kiwifruit at different ripening stages, obtaining a 100% original accuracy rate and a 99.4% cross-validation accuracy rate. Partial least squares regression (PLSR), support vector machine (SVM) and random forest (RF) were employed to build prediction models for overall ripeness, soluble solids content (SSC) and firmness. The regression results showed that the RF algorithm had the best performance in predicting the ripeness indexes of postharvest kiwifruit compared with PLSR and SVM, which illustrated that the E-nose data had high correlations with overall ripeness (training: R² = 0.9928; testing: R² = 0.9928), SSC (training: R² = 0.9749; testing: R² = 0.9143) and firmness (training: R² = 0.9814; testing: R² = 0.9290). This study demonstrated that E-nose could be a comprehensive approach to predict the ripeness of postharvest kiwifruit through aroma volatiles.

This paper presents a low-power megapixel image sensor design. In this paper, a column-parallel 11-bit two-step quantization scheme is proposed. It consists of a 3-bit single-slope analog-to-digital converter (ADC) and an 8-bit successive approximation register (SAR) ADC. The power consumption of the column-parallel circuitry is significantly reduced when compared with the traditional single-slope ADC and other low-power ADC schemes because smaller SAR ADC reference voltages are selected after quantizing the first three most significant bits. In addition, as only an 8-bit SAR ADC is required in the proposed quantization scheme, the capacitor array matching can be greatly relaxed compared with an 11-bit SAR ADC thus, resulting in noncalibration feature. A 1200 <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\,\times\,$</tex></formula> 800 pixel resolution color CMOS image sensor (CIS) is fabricated using TSMC 0.18- <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\mu{\rm m}$</tex> </formula> CIS technology. The measurement result shows that the total power consumption figure-of-merit of this research is only 1.33 mW/megapixel/frame under 3.3-V (analog)/1.8-V (digital) power supply.