W. Nicholson Price

Understanding the physical properties that control protein crystallization by analysis of large-scale experimental data.

Crystallization is the most serious bottleneck in high-throughput protein-structure determination by diffraction methods. We have used data mining of the large-scale experimental results of the Northeast Structural Genomics Consortium and experimental folding studies to characterize the biophysical properties that control protein crystallization. This analysis leads to the conclusion that crystallization propensity depends primarily on the prevalence of well-ordered surface epitopes capable of mediating interprotein interactions and is not strongly influenced by overall thermodynamic stability. We identify specific sequence features that correlate with crystallization propensity and that can be used to estimate the crystallization probability of a given construct. Analyses of entire predicted proteomes demonstrate substantial differences in the amino acid–sequence properties of human versus eubacterial proteins, which likely reflect differences in biophysical properties, including crystallization propensity. Our thermodynamic measurements do not generally support previous claims regarding correlations between sequence properties and protein stability.

Codon influence on protein expression in E. coli correlates with mRNA levels

Degeneracy in the genetic code, which enables a single protein to be encoded by a multitude of synonymous gene sequences, has an important role in regulating protein expression, but substantial uncertainty exists concerning the details of this phenomenon. Here we analyse the sequence features influencing protein expression levels in 6,348 experiments using bacteriophage T7 polymerase to synthesize messenger RNA in Escherichia coli. Logistic regression yields a new codon-influence metric that correlates only weakly with genomic codon-usage frequency, but strongly with global physiological protein concentrations and also mRNA concentrations and lifetimes in vivo. Overall, the codon content influences protein expression more strongly than mRNA-folding parameters, although the latter dominate in the initial ~16 codons. Genes redesigned based on our analyses are transcribed with unaltered efficiency but translated with higher efficiency in vitro. The less efficiently translated native sequences show greatly reduced mRNA levels in vivo. Our results suggest that codon content modulates a kinetic competition between protein elongation and mRNA degradation that is a central feature of the physiology and also possibly the regulation of translation in E. coli.

Informed consent for return of incidental findings in genomic research.

Purpose:Researchers face the dilemma of how to obtain consent for return of incidental findings from genomic research. We surveyed and interviewed investigators and study participants, with the goal of providing suggestions for how to shape the consent process.Methods:We performed an online survey of 254 US genetic researchers identified through the NIH RePORTER database, abstracts from the 2011 American Society of Human Genetics meeting, and qualitative semi-structured interviews with 28 genomic researchers and 20 research participants.Results:Most researchers and participants endorsed disclosure of a wide range of information about return of incidental findings, including risks, benefits, impact on family members, data security, and procedures, for return of results in the event of death or incapacity and for recontact. However, most researchers were willing to devote 30 min or less to this process and expressed concerns that disclosed information would overwhelm participants, a concern shared by many participants themselves.Conclusion:There is a disjunction between the views of investigators and participants about the amount of information that should be disclosed and the practical realities of the research setting, including the time available for consent discussions. This strongly suggests the need for innovative approaches to the informed consent process.Genet Med 16 5, 367–373.

Large-scale experimental studies show unexpected amino acid effects on protein expression and solubility in vivo in E. coli

The biochemical and physical factors controlling protein expression level and solubility in vivo remain incompletely characterized. To gain insight into the primary sequence features influencing these outcomes, we performed statistical analyses of results from the high-throughput protein-production pipeline of the Northeast Structural Genomics Consortium. Proteins expressed in E. coli and consistently purified were scored independently for expression and solubility levels. These parameters nonetheless show a very strong positive correlation. We used logistic regressions to determine whether they are systematically influenced by fractional amino acid composition or several bulk sequence parameters including hydrophobicity, sidechain entropy, electrostatic charge, and predicted backbone disorder. Decreasing hydrophobicity correlates with higher expression and solubility levels, but this correlation apparently derives solely from the beneficial effect of three charged amino acids, at least for bacterial proteins. In fact, the three most hydrophobic residues showed very different correlations with solubility level. Leu showed the strongest negative correlation among amino acids, while Ile showed a slightly positive correlation in most data segments. Several other amino acids also had unexpected effects. Notably, Arg correlated with decreased expression and, most surprisingly, solubility of bacterial proteins, an effect only partially attributable to rare codons. However, rare codons did significantly reduce expression despite use of a codon-enhanced strain. Additional analyses suggest that positively but not negatively charged amino acids may reduce translation efficiency in E. coli irrespective of codon usage. While some observed effects may reflect indirect evolutionary correlations, others may reflect basic physicochemical phenomena. We used these results to construct and validate predictors of expression and solubility levels and overall protein usability, and we propose new strategies to be explored for engineering improved protein expression and solubility.

Are trade secrets delaying biosimilars

Regulations for approving biologic drugs thwart the market for would-be competitors On 6 March 2015, the United States Food and Drug Administration (FDA) approved, under the Biologics Price Competition and Innovation Act (BPCIA), a biosimilar of filgrastim (Neupogen), for treating chemotherapy-caused neutropenia (1). Although this action represents a step toward cheaper medical treatments, it masks systemic problems. Not only has it taken 5 years since the BPCIAs passage (2), but economists estimate that even by 2020, biosimilar competition will reduce consumer prices only modestly (3). Why will price competition be so lacking? One key reason is the barrier to competitive entry created by trade secrecy in biologics manufacturing.

Making Do in Making Drugs: Innovation Policy and Pharmaceutical Manufacturing

Drug recalls, contamination events, and shortages are on the rise, but drug companies still rely on decades-old manufacturing plants and processes. Contrary to widespread perceptions, drug manufacturing is typically expensive, inefficient, and non-innovative. Drug companies spend much more on manufacturing than on research and development, but the industry lags far behind the innovative manufacturing found in other industries. This lack of innovation in drug manufacturing stands in stark contrast to the innovation present in drug discovery. Drug discovery is the focus of a calibrated innovation policy that combines patents and the regulatory regime. Manufacturing lacks such attention, and the costs are great, both in dollars and in human lives. This article addresses the previously underappreciated role of manufacturing in innovation studies and policy. The stagnation of pharmaceutical manufacturing results from regulatory barriers and ineffective intellectual-property incentives. As a result of the difficulty enforcing manufacturing process patents, manufacturers tend to rely on trade secrecy instead, which reduces innovation. Making matters worse, regulation actively impedes innovative changes to manufacturing methods through substantive and procedural barriers across the lifespan of a drug. To address these challenges, this article suggests several direct regulatory reforms. It also proposes novel ways that regulation can be used to change the function of intellectual property incentives, which fit particularly well in the drug manufacturing context but could be extended to different areas of innovation policy. For example, FDA could be charged with operating a system of temporary market exclusivity for manufacturing innovation parallel to the patent system. Alternately, FDA could require disclosure of manufacturing methods to drive the industry from opacity and trade secrecy towards transparency and patent protection for innovation. A better targeted and more effective innovation policy could improve the current sad state of drug manufacturing with potentially immense economic and health benefits.

The Need for a Privacy Standard for Medical Devices That Transmit Protected Health Information Used in the Precision Medicine Initiative for Diabetes and Other Diseases

Privacy is an important concern for the Precision Medicine Initiative (PMI) because success of this initiative will require the public to be willing to participate by contributing large amounts of genetic/genomic information and sensor data. This sensitive personal information is intended to be used only for specified research purposes. Public willingness to participate will depend on the public’s level of trust that their information will be protected and kept private. Medical devices may constantly provide information. Therefore, assuring privacy for device-generated information may be essential for broad participation in the PMI. Privacy standards for devices should be an important early step in the development of the PMI.

Will clinical trial data disclosure reduce incentives to develop new uses of drugs

To the Editor: Last October, the European Medicines Agency (EMA) adopted a new policy that clinical study reports (CSRs) submitted as part of a marketing application in 2015 or later will be published—with redactions of commercially confidential information— once a decision is made on the application1. Earlier in 2014, the European Parliament and Council passed a regulation to similar effect2. Meanwhile, the US Food and Drug Administration (FDA) has proposed new rules that would require disclosure of masked and de-identified patient-level data3. The drug industry has responded with its own transparency projects, including initiatives by GlaxoSmithKline, AstraZeneca, Sanofi, Pfizer and others4. These developments reflect a growing policy consensus favoring disclosure, which promotes independent verification of drug safety and efficacy data, provides a better framework for precompetitive collaboration and increases public trust in drugs and industry and the possibility of facilitating large crossborder clinical trials for, inter alia, rare diseases5. Despite these benefits, the costs and concerns associated with opening up trial data are also substantial—for patients (patient privacy), for research (related to misuse of clinical trial data in poor-quality analyses) and for industry (fewer incentives to invest in innovative R&D owing to reduced competitive edge and increased exposure to litigation owing to trolling of these data by class-action tort lawyers)6. Here we highlight another area where clinical trial disclosure may have adverse effects: the development of new uses for already approved drugs5. Drugs frequently have multiple effects; for instance, interferon-a, developed to treat hairy-cell leukemia, is now also used to treat hepatitis C and metastatic melanoma5. Finding and developing additional medical uses for older drugs minimizes concerns about whether a physiologically potent molecule can be made into a safe, stable drug7. In principle, human trial disclosure should help this goal: with more carefully controlled drug data, third-party drug companies or independent researchers can identify new uses for testing and development. However, many new uses would still require costly clinical trials to receive market approval. Firms typically only make such investments if they can expect a sufficient exclusivity period after approval5. And herein lies the challenge: clinical trial disclosure severely limits the patentability of new uses in both the United States and the European Union. Under US law, methods of new drug uses can only be patented if the use has not been disclosed publicly. A disclosure focusing on one treatment but revealing another effect will block later patents on that use; for example, an article describing a method of skin treatment that noted the disruption of hair follicles was enough to block a patent on using the method for hair depilation8. Applied to the issue of clinical trial disclosure, if a drug in clinical trials had a second effect that was noted and disclosed in a CSR, it would probably be impossible to later patent the second use of the drug (Fig. 1). Even for uses not precisely disclosed, a second use, if it would be obvious to someone skilled in the relevant field, would be unpatentable. Under European law the effect is the same, although through slightly different reasoning. Although Article 54 (4) & (5) of the European Patent Convention allows patenting of a known product’s new medical uses, these uses must still demonstrate novelty and an inventive step under Articles 52 and 56, as determined in the European Patent Office’s decisions in T128/82 (PyrrolidinDerivate)9 and G2/08 (Dosage regime/Abbott Respiratory)10. New and non-obvious uses discovered during clinical trials would still be patentable. Frequently, though, such uses are discovered

Promoting Healthcare Innovation on the Demand Side

Abstract Innovation policy often focuses on fortifying the incentives of firms that develop and sell new products by offering them lucrative rights to exclude competitors from the market. Regulators also rely on these same firms—and on similar incentives—to develop information about the effects of their products in patients, despite their obvious conflict of interest. The result may be a distorted understanding that leads to overuse of expensive new medical technologies. Recent technological advances have put healthcare payers in an excellent position to play a larger role in future innovation to improve healthcare and reduce its costs. Insurance companies and integrated healthcare providers have custody of treasure troves of data about healthcare provision and outcomes that can yield valuable insights about the effects of medical treatment without the need to conduct costly clinical trials. Some integrated healthcare systems have seized upon this advantage to make notable discoveries about the effects of particular products that have changed the standard of care. Moreover, to the extent that healthcare payers can profit from reducing costs, they will seek to avoid inappropriate use of costly technologies. Greater involvement of payers in healthcare innovation thus offers a potential counterweight to the incentives of product sellers to promote excessive use of costly new products. In recent years, the federal government has sought to promote innovation through analysis of healthcare records in a series of initiatives; some picture insurers as passive data repositories, while others provide opportunities for insurers to take a more active role in innovation. In this paper, we examine the role of health insurers in developing new knowledge about the provision and effects of healthcare—what we call ‘demand-side innovation’. We address the contours of this underexplored area of innovation and describe the behavior of participating firms. We examine the effects of current legal rules on demand-side innovation, including insurance regulation, intellectual property rules, privacy protections, and FDA regulation of new healthcare technologies. Throughout, we highlight many policy tools that government can use and is using to facilitate payer innovation outside the traditional toolkit of patents and exclusive rights.

Risk and Resilience in Health Data Infrastructure

Today’s health system runs on data. However, for a system that generates and requires so much data, the health care system is surprisingly bad at maintaining, connecting, and using those data. In the easy cases of coordinated care and stationary patients, the system works — sometimes. But when care is fragmented, fragmented data often result. Fragmented data create risks both to individual patients and to the system. For patients, fragmentation creates risks in care based on incomplete or incorrect information, and may also lead to privacy risks from a patched-together system. For the system, data fragmentation hinders efforts to improve efficiency and quality, and to drive health innovation based on collected data. Efforts to combat data fragmentation would benefit by considering the idea of health data infrastructure. Most obviously, that would be infrastructure for health data — that is, infrastructure on which health data can be stored and transmitted. But it should also be an infrastructure of health data — that is, a platform of shared data on which to base further efforts to increase the efficiency or quality of care.