Page 34 - Genomic Medicine in Emerging Economies

Overcoming Barriers to Implementing Genomic Medicine in Developing Countries 23

among members of research ethics or scientific review committees for whom
genomics may be a relatively new concept, and for whom genomics raises con-
cerns because of lack of familiarity.

j Train data scientists and provide access to both data and genetic
resources.

Bioinformaticians and data scientists are a commodity in any part of the world.
The demand for such professionals will grow exponentially in the coming
years. To keep abreast with this demand, education and training in the basics
of genomics and bioinformatics will have to be introduced at the level of sec-
ondary education, while more advanced training can be at the undergraduate
and graduate levels (Cohn et al., 2015). Access to genomic data manipulation
and analysis tools is essential for providing such training. Although many bio-
informatics tools are distributed under different open-source licenses, many
advanced tools that are sold by companies require complicated licensing pro-
cedures to be used. Such licensure fees are frequently too expensive for institu-
tions in the developing world.
Having access to up-to-date literature is crucial for those working in fields such
as genomic medicine. The recent growth of open-access publications has greatly
assisted in making contemporary literature available to scientists from devel-
oping countries. However, highly respected journals that require subscription
fees are unaffordable for developing countries. This means that important new
knowledge is inaccessible. In addition, genomic data download and manipula-
tion require fast and stable Internet connections that are not always available
in developing countries. Steps have to be taken to overcome these challenges.

j Provide avenues for management/integration of genomic data into
clinical delivery and sharing of de-identified data.

One factor that is preventing the wider practice of genomic medicine in
routine clinical practice is the limitation in our current understanding of
the clinical relevance and predictive value of the genomic variants detected
by NGS, and the implications of false-positive results (Adams et al., 2016;
Bodian et al., 2014). The sharing of genomic data among scientists across
borders is essential therefore for understanding the clinical implications of
genomic variants. Reevaluation of the patchy literature regarding disease vari-
ants depends on continued data sharing and standardization of reporting
(Manrai et al., 2016). It is therefore imperative to train data scientists and
provide access to both genetic resources and sharing of de-identified data as
well as provide avenues for genomic data management and integration into
clinical delivery systems.
j Foster multidisciplinary collaborations of genomics research and
services.