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    Digging deeper into precision/personalized medicine: cracking the sugar code, the third alphabet of life, and sociomateriality of the cell
    (Mary Ann Liebert, Inc, 2020) Özdemir, Vural; Arga, K. Yalçın; Aziz, Ramy K.; Bayram, Mustafa; Conley, Shannon N.; Dandara, Collet; Endrenyi, Laszlo; Fisher, Erik; Garvey, Colin K.; Hekim, Nezih; Kunej, Tanja; Şardaş, Semra; Von Schomberg, Rene; Yassin, Aymen S.; Yılmaz, Gürcim; Wang, Wei
    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.
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    To genotype or phenotype for drug and food safety? Exiting the technology echo chambers
    (Mary Ann Liebert, Inc, 2018) Özdemir, Vural; Endrenyi, Laszlo; Hekim, Nezih; Kunej, Tanja; Steuten, Lotte M.; Springer, Simon; Şardaş, Semra; Ergüler, Erol; Bayram, Mustafa
    Scholars throughout history have argued there is nothing more important than understanding and explaining the world that we live in. Both scientists and social scientists share this motivation. Yet, they employ different tools and viewpoints. Scientists and technology experts tend to focus on ‘‘doing science’’ and related questions, such as ‘‘which knowledge is being produced?’’ Social and political science scholars ask questions relating to ‘‘how we do science.’’ Such differences in the types of knowledges that are produced and sought after also create values that differ between scientists and social scientists. Scientists might value, for example, which technology and biomarker are available for cancer precision medicine, whereas social scientists would like to know the epistemology of scientific knowledge: how do we know what we know? Who is funding and producing biomarker knowledge, and to what ends?