Rethinking Clinical Trials and Personalized Medicine with Placebogenomics and Placebo Dose.

Pharmacogenomics, nutrigenomics, vaccinomics, and the nascent field of plant omics are examples of variability science. They are embedded within an overarching framework of personalized medicine. Across these public health specialties, the significance and biology of the placebo response have been historically neglected. A placebo is any substance such as a sugar pill administered in the guise of medication, but one that does not have pharmacological activity. Placebos do have clinical effects, however, that can be substantive in magnitude and vary markedly from person-to-person depending, for example, on the type of disease, symptoms, or clinical trial design. Research over the past several decades attests to a genuine neurobiological basis for placebo effects. All drugs have placebo components that contribute to their overall treatment effect. Placebos are used in clinical trials as control groups to ascertain the net pharmacological effect of a drug candidate. Not only less well known but also relevant to rational therapeutics and personalized medicine is the nocebo. A nocebo effect occurs when an inert substance is administered in a context that induces negative expectations, worsening patients' symptoms. With the COVID-19 pandemic, there are high public expectations for new vaccines and medicines to end the contagion, while at the same time antiscience, post-truth, and antivaccine movements are worrisomely on the rise. These social movements, changes in public health cultures, and conditioned behavioral responses can trigger both placebo and nocebo effects. Hence, in clinical trials, forecasting and explaining placebo and nocebo variability are more important than ever for robust science and personalized health care. Against this overarching context, this article provides (1) a brief history of placebo and (2) a discussion on biology, mechanisms, and variability of placebo effects, and (3) discusses three emerging new concepts: placebogenomics, nocebogenomics, and augmented placebo, that is, the notion of a "placebo dose." We conclude with a roadmap for placebogenomics, its synergies with the nascent field of social pharmacology, and the ways in which a new taxonomy of drug and placebo variability can be anticipated in the next decade.

Digging Deeper into Precision/Personalized Medicine: Cracking the Sugar Code, the Third Alphabet of Life, and Sociomateriality of the Cell.

Precision/personalized medicine is a hot topic in health care. Often presented with the motto "the right drug, for the right patient, at the right dose, and the right time," precision medicine is a theory for rational therapeutics as well as practice to individualize health interventions (e.g., drugs, food, vaccines, medical devices, and exercise programs) using biomarkers. Yet, an alien visitor to planet Earth reading the contemporary textbooks on diagnostics might think precision medicine requires only two biomolecules omnipresent in the literature: nucleic acids (e.g., DNA) and proteins, known as the first and second alphabet of biology, respectively. However, the precision/personalized medicine community has tended to underappreciate the third alphabet of life, the "sugar code" (i.e., the information stored in glycans, glycoproteins, and glycolipids). This article brings together experts in precision/personalized medicine science, pharmacoglycomics, emerging technology governance, cultural studies, contemporary art, and responsible innovation to critically comment on the sociomateriality of the three alphabets of life together. First, the current transformation of targeted therapies with personalized glycomedicine and glycan biomarkers is examined. Next, we discuss the reasons as to why unraveling of the sugar code might have lagged behind the DNA and protein codes. While social scientists have historically noted the importance of constructivism (e.g., how people interpret technology and build their values, hopes, and expectations into emerging technologies), life scientists relied on the material properties of technologies in explaining why some innovations emerge rapidly and are more popular than others. The concept of sociomateriality integrates these two explanations by highlighting the inherent entanglement of the social and the material contributions to knowledge and what is presented to us as reality from everyday laboratory life. Hence, we present a hypothesis based on a sociomaterial conceptual lens: because materiality and synthesis of glycans are not directly driven by a template, and thus more complex and open ended than sequencing of a finite length genome, social construction of expectations from unraveling of the sugar code versus the DNA code might have evolved differently, as being future-uncertain versus future-proof, respectively, thus potentially explaining the "sugar lag" in precision/personalized medicine diagnostics over the past decades. We conclude by introducing systems scientists, physicians, and biotechnology industry to the concept, practice, and value of responsible innovation, while glycomedicine and other emerging biomarker technologies (e.g., metagenomics and pharmacomicrobiomics) transition to applications in health care, ecology, pharmaceutical/diagnostic industries, agriculture, food, and bioengineering, among others.

A New Approach to Measure Adherence to Medicines Using Biomarkers and Sensors.

Approximately one in two patients with a chronic disease does not take their medicines as prescribed. Poor adherence is a worldwide epidemic and a major source of variability in pharmacokinetics (PK) and pharmacodynamics. Without addressing adherence, precision medicine is unlikely to come to fruition. In drug development, poor adherence confounds the estimates for efficacy and safety of drug candidates. Accurate and high-resolution measurement of adherence is a first step toward effective interventions against poor adherence. We describe a new cross-technology platform to measure adherence. The approach involves, first, building PK models to explain dose-exposure relationships. The model incorporates PK biomarkers by genotyping or phenotyping of drug metabolism, transport and other drug clearance pathways. Importantly, dose-exposure data for model building are obtained in healthy volunteer and/or patient cohorts who are ascertained for full adherence, using edible ingestion sensors (IS) that digitize orally administered medicines. Second, the built model is harnessed to back calculate the dose actually ingested by patients, given the empirically observed drug exposure, PK biomarker, demographic, and other patient data. The proposed platform is envisioned to result in development of both drug and drug-specific companion software for adherence measurement. In terms of feasibility, the new approach overlaps with current drug development timelines spanning the Phase 1 to 4 clinical trial continuum, and thus, could conceivably be implemented without requiring significant changes to the time sensitive clinical trial processes. For the IS-powered tools, the proposed platform creates a new space for applications in clinical trials to ensure adherence.

Interchangeability Of Biological Drug Products-FDA Draft Guidance.

The Biological Price Competition and Innovation Act (BPCI Act) of 2009 established a pathway for the approval of biosimilars and interchangeable biosimilars in the United States. The Food Drug Administration (FDA) has issued several guidances on the development and assessment of biosimilars which implement the BPCI Act. In particular, a recent draft guidance on the interchangeability of biological products presents an overview of scientific considerations on the demonstration of interchangeability with a reference product. The present communication provides a general summary of the draft guidance and briefly observes a few current issues on interchangeability.

Panos Macheras: a pioneering scientist in pharmaceutical science.

Professor Panos Macheras is a pioneering scientist in pharmacokinetics, pharmacodynamics and biopharmaceutics. His many important contributions to pharmaceutical science are reviewed.

Bioequivalence for highly variable drugs: regulatory agreements, disagreements, and harmonization.

Regulatory authorities introduced procedures in the last decade for evaluating the bioequivalence (BE) for highly variable drugs. These approaches are similar in principle but differ in details. For example, the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) recommend differing regulatory constants. The constant suggested by FDA results in discontinuity of the BE limits around the switching variation at 30% observed within-subject variation of the reference product. The regulatory constant of EMA does not have these problems. The Type I error reaches 6-7% around the switching variation with the EMA constant but 16-17% with the FDA constant. Various procedures were recently suggested, especially for the EMA approach, to eliminate the inflation of the Type I error. Notably, the so-called Exact algorithms try to amalgamate the positive features of both EMA and FDA procedures without their negative sides. The computational procedure for the EMA approach is simple and has a straightforward interpretation. The procedure for the FDA approach is based on an approximation, has a bias at small degrees of freedom, and requires a suitable computer program. All regulatory agencies impose a second requirement constraining the point estimate of the ratio of geometric means. In addition, EMA and Health Canada impose an upper limit for applying the recommended procedures. These expectations have psychological motivation and political rationale but no scientific foundations. Their inclusion results in incorrect and misleading interpretation of the principal criterion which involves confidence intervals. Different regulatory authorities expect to apply their approaches either to both AUC and Cmax or only to AUC or only to Cmax. Rational resolution of the disharmonization is needed.

Summary report of second EUFEPS/AAPS conference on global harmonization in bioequivalence.

The Global Bioequivalence Harmonization Initiative (GBHI) was launched by the Network on Bioavailability and Biopharmaceutics (BABP) under the auspices of European Federation for Pharmaceutical Sciences (EUFEPS) several years ago. Since 2015, EUFEPS in collaboration with the American Association of Pharmaceutical Scientists (AAPS) has organized three international conferences to support global harmonization of regulatory requirements for bioequivalence (BE) assessment. These conferences provided an open forum for pharmaceutical scientists from academia, industry and regulatory agencies to discuss various BE topics at issue. The current report summarizes the discussion of BE issues at the 2nd GBHI conference held in 2016, Rockville, USA. Three important BE topics were discussed at the meeting: (a) prodrugs and compounds with pre-systemic extraction, (b) scaling procedures and two-stage designs, and (c) exclusion of pharmacokinetic data in BE assessment. The presentations and discussions of these issues have enhanced the mutual understanding of scientific background for BE evaluation and further facilitated harmonization of regulatory approaches for establishing BE of multisource drug products.

Stop the Spam! Conference Ethics and Decoding the Subtext in Post-Truth Science. What Would Denis Diderot Say?

Science and its practice always had a subtext, subject to influence by scientists', funders', and other innovation actors' values and assumptions. The recent emergence of post-truth, authoritarian and populist penchants, in both developed and developing countries, has further blurred the already fluid boundaries between material scientific facts and their social construction/shaping by scientific subtext, human values, powers, and hegemony. While there are certain checks, balances, and oversight mechanisms for publication ethics, other pillars of science communication, most notably, scientific conferences and their governance, are ill prepared for post-truth science. Worrisomely, the proliferation of spam conferences is a major cause for concern for integrative biology and postgenomic science. The current gaps in conference ethics are important beyond science communication because conferences help build legitimacy of emerging technologies and frontiers of science and, thus, bestows upon the organizers, funders, enlisted scientific advisors, speakers, among others, power, which in turn needs to be checked. Denis Diderot (1713-1784), a prominent intellectual during the Enlightenment period, has aptly observed that the very act of organizing brings about power, influence, and control. If the subtext of conference practices is left unchecked, it can pave the way for hegemony, and yet more volatile and violent authoritarian governance systems in science and society. This begs for innovative solutions to increase accountability, resilience, and capacity of technology experts and scientists to discern and decode the subtext in science and its communication in the current post-truth world. We propose that the existing undergraduate and graduate programs in life and physical sciences and medicine could be redesigned to include a rotation for exposure to and training in political science. Such innovative PhD+ programs straddling technical and political science scholarship would best equip future students and citizens to grasp and respond to subtext and embedded opaque value and power systems in scientific practices in an increasingly post-truth world. Political science scholarship unpacks the inner workings, subtext, and power dynamics in science and society. Thus, knowledge of political science competency is akin to molecular biology in life sciences. Both make the invisible (e.g., cell biology versus subtext of knowledge) visible. The ability to read subtext in science and claims of post-truth knowledge is a new and essential form of societal literacy in 21st century science and integrative biology.

Algorithms for evaluating reference scaled average bioequivalence: power, bias, and consumer risk.

The determination of the bioequivalence between highly variable drug products involves the evaluation of reference scaled average bioequivalence. The European and US regulatory authorities suggest different algorithms for the implementation of this approach. Both algorithms are based on approximations reflected in lower than the achievable power or higher than the nominal consumer risk of 5%. To overcome these deficiencies, a new class of algorithms, the so-called Exact methods, was earlier introduced. However, their applicability was limited. We propose 2 modifications which make their computation simpler and also applicable with any study design. Four algorithms were evaluated in simulated 3-period and 4-period bioequivalence studies: Hyslop's approach recommended by the US FDA, the method of average bioequivalence with expanding limits requested by the European EMA, and 2 versions of the new Exact methods. At small sample sizes, the Exact methods had substantially higher statistical power than Hyslop's algorithm and had lower consumer risk than the method of average bioequivalence with expanding limits. Similarly to the Hyslop's algorithm, higher than 5% consumer risk was observed only with either unbalanced study design or with additional regulatory requirements. The improved Exact algorithms compare favorably with the alternative procedures. They are based on the bias correction method of Hedges. The recognition that the scaled difference statistics is measured with bias has important practical implications when results of pilot bioequivalence studies are evaluated and, at the same time, calls for the revision of the statistical theory of RSABE and its related methods.

The Two Main Goals of Bioequivalence Studies.

The principal goal of bioequivalence (BE) investigations has crucial importance and has been the subject of extensive discussions. BE studies are frequently considered to serve as procedures for sensitive discrimination. The BE investigation should be able to provide methods and conditions sensitively identifying relevant differences between drug products if such differences in fact exist. Alternatively, BE studies can be deemed as surrogates of clinical investigations assessing therapeutic equivalence. Bioequivalent drug products will be provided to patients for their benefits. Both points of view are valid since they represent two aspects of product performance. It has been argued that both should be equally sustained and applied. In practice, however, they collide when regulatory conditions and statements are developed. For instance, some regulators prefer to conduct BE studies following single drug administrations since these conditions are considered to provide the highest sensitivity of discrimination between pharmacokinetic profiles and thus, a product's in-vivo performance. Others suggest that, at least for modified-release products, BE investigations should be performed in the steady state since it represents clinical conditions. Preference for one point of view or the other pervades other regulatory statements including suggestions for subjects to be selected in studies and pharmacokinetic measures to be evaluated. An overview is provided on the disturbing inconsistency of statements within and between regulations. It is argued that harmonization would be highly desirable, and relevant recommendations are offered.

An Exact Procedure for the Evaluation of Reference-Scaled Average Bioequivalence.

Reference-scaled average bioequivalence (RSABE) has been recommended by Food and Drug Administration (FDA), and in its closely related form by European Medicines Agency (EMA), for the determination of bioequivalence (BE) of highly variable (HV) and narrow therapeutic index (NTI) drug products. FDA suggested that RSABE be evaluated by an approximating procedure. Development of an alternative, numerically exact approach was sought. A new algorithm, called Exact, was derived for the assessment of RSABE. It is based upon the observation that the statistical model of RSABE follows a noncentral t distribution. The parameters of the distribution were derived for crossover and parallel-group study designs. Simulated BE studies of HV and NTI drugs compared the power and consumer risk of the proposed Exact method with those recommended by FDA and EMA. The Exact method had generally slightly higher power than the FDA approach. The consumer risks of the Exact and FDA procedures were generally below the nominal error risk with both methods except for the partial replicate design under certain heteroscedastic conditions. The estimator of RSABE was biased; simulations demonstrated the appropriateness of Hedges' correction. The FDA approach had another, small but meaningful bias. The confidence intervals of RSABE, based on the derived exact, analytical formulas, are uniformly most powerful. Their computation requires in standard cases only a single-line program script. The algorithm assumes that the estimates of the within-subject variances of both formulations are available. With each algorithm, the consumer risk is higher than 5% when the partial replicate design is applied.

Subsequent Entry Biologics in Canada: Current State of the Science.

The Canadian Society for Pharmaceutical Sciences organized a workshop on the current state of sciences of subsequent entry biologics (SEBs, biosimilars) on December 10th 2014 in the Health Canada location in Ottawa, ON. The day-long workshop provided an opportunity to discuss recent regulatory developments and a wide range of scientific issues related to SEBs. Following a discussion on the differences between the Canadian guidance and those of other countries,  a series of presentations were made that focused on the regulatory requirements with regard to the product quality, methodology, non-clinical and clinical data. In addition, issues of extrapolation from one indication to another, interchangeability and reimbursement  were articulated. It was also highlighted that both the patients and caregivers need to be better informed regarding the safety and efficacy of articulated SEBs.

An Appeal to the Global Health Community for a Tripartite Innovation: An "Essential Diagnostics List," "Health in All Policies," and "See-Through 21(st) Century Science and Ethics".

Diagnostics spanning a wide range of new biotechnologies, including proteomics, metabolomics, and nanotechnology, are emerging as companion tests to innovative medicines. In this Opinion, we present the rationale for promulgating an "Essential Diagnostics List." Additionally, we explain the ways in which adopting a vision for "Health in All Policies" could link essential diagnostics with robust and timely societal outcomes such as sustainable development, human rights, gender parity, and alleviation of poverty. We do so in three ways. First, we propose the need for a new, "see through" taxonomy for knowledge-based innovation as we transition from the material industries (e.g., textiles, plastic, cement, glass) dominant in the 20(th) century to the anticipated knowledge industry of the 21st century. If knowledge is the currency of the present century, then it is sensible to adopt an approach that thoroughly examines scientific knowledge, starting with the production aims, methods, quality, distribution, access, and the ends it purports to serve. Second, we explain that this knowledge trajectory focus on innovation is crucial and applicable across all sectors, including public, private, or public-private partnerships, as it underscores the fact that scientific knowledge is a co-product of technology, human values, and social systems. By making the value systems embedded in scientific design and knowledge co-production transparent, we all stand to benefit from sustainable and transparent science. Third, we appeal to the global health community to consider the necessary qualities of good governance for 21st century organizations that will embark on developing essential diagnostics. These have importance not only for science and knowledge-based innovation, but also for the ways in which we can build open, healthy, and peaceful civil societies today and for future generations.

Scientific factors and current issues in biosimilar studies.

Biological drugs are much more complicated than chemically synthesized, small-molecule drugs; for instance, their size is much larger, their structure is more complicated, they can be sensitive to environmental conditions such as temperature or pressure, and they may expose patients to immunogen reactions. Consequently, the assessment of biosimilarity calls for greater circumspection than the evaluation of bioequivalence. The present communication discusses scientific factors and some current issues related to biosimilarity and the interchangeability of drug products. The scientific factors include questions involving endpoint selection, the one-size-fits-all criterion, and the need for a more flexible approach, e.g., evaluation of the degree of similarity (i.e., responding to the question of "how similar is similar?"; a review of study designs that are useful for the assessment of biosimilarity and drug interchangeability; and tests for the comparability of critical quality attributes at various stages of the manufacturing process). Current issues include the choice of reference standards and the relevant study designs; criteria for biosimilarity, as well as for interchangeability and for comparability; the determination of the noninferiority margin; and the concepts of the stepwise approach to biosimilarity studies and of their assessment by the totality of the evidence. The calculation of sample sizes is discussed for crossover (including some higher-order schemes) and parallel designs.