DOI: 10.6078/d1nm58
title: The capacity challenge: Governing in an era of rapid scientific, technological, and economic change

description: In this research, we examined how public regulatory agencies respond to
 rapidly emerging technologies. Our study examined the role of the Food and
 Drug Administration as it manages first-in-human clinical trials using
 CRISPR/Cas-9 gene editing technologies and we examined both state and
 federal regulators who are managing the introduction of connected and
 autonomous vehicle (CAV) technologies. The research builds on a concept of
 "absorptive capacity" that examines the types of investments
 firms make in fields of rapidly emerging technologies that allow them to
 remain competitive. Prior to our study, this concept had not been applied
 in the public sector. We found that public sector agencies, when they have
 the budget to do so, make similar kinds of investments to ensure that they
 can perform their legislatively mandated roles.  Because public
 sector agencies are sometimes constrained in their ability to make such
 investments (e.g., lack of budget; barriers to recruitment), many agencies
 find creative ways to bolster their own technical capacity. In fact, this
 can be a preferred strategy when building up internal capacity might take
 too much time. Our research indicates that the public sector agencies
 asked to determine, as a matter of public policy, the likely risks and
 benefits of CRISPR/Cas-9 and CAV emerging technologies bring significant
 expertise to the table and, in many cases, do not lag their private sector
 counterparts in their technical understanding of the technologies they are
 asked to review. An important feature of our research is that we studied
 agencies that, because they provide access to markets for new
 technologies, often have the support of regulated actors who enjoy the
 benefits of having received a stamp of safety or effectiveness. 
 We believe that this support from the regulated sector may be important in
 providing agencies with the resources, including political legitimacy,
 they need to be able to maintain expertise. The research findings are
 based on interviews with private sector actors in the process of
 developing CRISPR/Cas-9 medical treatments or CAV technologies and with
 agency personnel at the state and federal level. 
description: This data stems from 33 in-depth interviews with regulatory
 experts and innovators leading CAV (14) and CRISPR-Cas9 (19) technological
 development. This includes interviews with regulatory reviewers and those
 who have experience working with government agencies such as the FDA,
 Department of Transportation, and Department of Motor Vehicles, as well as
 individuals working in technology innovation including leaders of private
 biotechnology or automobile development companies, consulting agencies,
 academic and industry scientific researchers, and legal experts.
 Interviews were semi-structured and typically lasted an hour, with a few
 closer to two hours. These interviews took place via various mediums –
 in-person, over the phone, and video conferencing – in order to
 efficiently accommodate interviewees across the United States. During
 interviews, individuals were asked about their perspectives regarding the
 technology, CRISPR-Cas9 or CAVs, specifically pertaining to future
 development, priorities and concerns for regulation, and potential risks.
 Each interviewee who consented to audio recording was provided with the
 opportunity to review their de-identified transcript before it became a
 part of this public repository of collected data. The
 sample of interviewees for this study consist of a combination of
 purposive samples, from targeted search strategies, and snowball samples
 resulting from references from interviewees. This approach to sampling
 allowed us to reach experts who are otherwise challenging to connect with
 and enlist for academic data collection, especially given the high-level,
 often private and proprietary nature of their work. In order to record
 perspectives from the gamut of stakeholders, we purposefully searched for
 interviewees who had relevant technological or regulatory experience and
 were affiliated with related organizations. Further, our team’s ability to
 network with relevant experts was bolstered by our location near to a
 substantial number of laboratories, research hospitals, technology and
 regulatory consultants, and private companies innovating genomic and
 automated vehicle technologies. The target population of interviewees thus
 consisted of employees or ex-employees working at government agencies and
 private companies that inform the development and regulation of CAVs and
 CRISPR-Cas9 for biomedical purposes. The sampling frame consisted of
 public directories and meeting rosters of those sitting on regulatory
 advisory committees (i.e. the FDA’s Cellular, Tissue, and Gene Therapies
 Advisory Committee), professional societies (i.e. American Society of Gene
 & Cell Therapy), and private stakeholders with expertise
 navigating the regulatory landscape for genome editing and automated
 vehicles. We also utilized LinkedIn search functionalities, which allowed
 us to identify and reach out to individuals with relevant expertise,
 employer histories, and professional trajectories. Because a significant
 focus of this study was concerned with government regulatory agencies,
 target individuals’ contact information was often publicly listed. Our
 team contacted all relevant individuals. We interviewed all those who
 agreed to be a respondent. Most interviewees also provided a list of
 references for further interviews, generating a snowball sample in
 addition to the purposive sample. Almost all
 interviewees provided consent to be audio recorded. Using this audio
 recording, accurate transcripts were generated by a professional human
 transcription service and then de-identified by the research team to the
 standard described below. Per our human subjects
 approval letter, which subjects were able to review prior to consenting to
 an interview and inclusion in the repository, transcripts were
 de-identified to the following standard: "the research team will
 review transcripts to ensure that they contain no information that would
 allow a reasonably knowledgeable and determined person to identify the
 individual who gave the interview." Redactions made to the interview
 transcripts are marked in the text with [redacted] where
 applicable.
description: As described in the methods section, this dataset is comprised of
 de-identified interview transcripts from 33 interviews. All subjects were
 given the option to consent to inclusion or opt for exclusion of their
 redacted transcript in the repository at the time of the interview and
 again upon review of the redacted transcripts. Based on
 this review process, 14 of the 33 interviews are included in this
 repository (9 CRISPR and 5 CAV). All interviews conducted (including those
 which are NOT in the repository) are indexed in the overview file for
 citation and reference purposes. Files:
 README.xlsx Description: Master
 overview file of the entire interview dataset, including meta-data for
 interviews which are not included in the repository)
 Columns:  Interview Number (serves as
 GUID) Month Year
 Case (CAV or Gene Therapy (GT) In
 Repository? (Included or Excluded)
 Filename 
 De-Identified Interview Transcripts 
 One .docx and one PDF per interview (PDF for stable page
 numbering, docx for easy restructuring) Naming
 convention: Capacity Challenge_Interview [Interview Number]_[Case
 Abbreviation CAV or GT]_[Month][Year] i.e. Capacity
 Challenge_Interview 1_CAV_07-2018.docx AND Capacity Challenge_Interview
 1_CAV_July2018.pdf Total
 number of interview transcripts: 14 
 Recommend In-Text Citation style for
 interviews: (Posch et al. 2021, Interview #, page [#
 from PDF]) i.e. (Posch et al. 2021, Interview 1, page
 4)