One of the key goals of the Genomic Medicine Alliance is to encourage and catalyze multidisciplinary collaborative research between partner institutions and scientists, particularly from emerging countries and to establish collaboration ties among research organizations, clinical entities and regulatory agencies in areas related to genomic medicine.

The members of the Genomic Medicine Alliance have so far established the following working groups:

• Genome Informatics
• Genomics & Pharmacogenomics
• Public Health Genomics
• Health Economics

The Genomic Medicine Alliance is a global academic research network which aims to build and strengthen collaborative ties between academics, researchers, regulators and also members from the general public interested in genomic and personalized medicine. 

Since its establishment, the number of its members has expanded at a very rapid pace. Currently it consists of over 1.300 members (January 2018) from more than 70 countries worldwide. The Genomic Medicine Alliance members are coming from academia as well as from corporate and regulatory sectors, including developing countries and low-resources environments* in the Middle East, Asia and Latin America.

The primary goal of Genomic Medicine Alliance is the development of a network focusing on the translation of genomic knowledge into clinical practice. The key points that make Genomic Medicine Alliance different from existing consortia, research networks and initiatives in this field are:

- Membership is free of charge,

- Flat governance structure, 

- Commitment to bring together genomics research institutions form developing countries with those from developed countries.

The Genomic Medicine Alliance fosters collaboration in genomics research between developed and developing countries providing benefits to both sides. Developing countries could benefit from training opportunities, knowledge exchange and expanding transnational networks. On the other hand, developed countries expect to benefit through comparative work by having access to ethnically diverse populations, families with rare diseases or unique clinical features.

In particular, the Genomic Medicine Alliance aims to:

• Encourage and catalyze multidisciplinary collaborative research between partner institutions and scientists, particularly from emerging countries.
• Liaise among research organizations, clinical entities and regulatory agencies in areas related to genomic medicine.
• Facilitate the introduction of pharmacogenomics and advanced omics technologies into the mainstream clinical practice.
• Produce and propose guidelines and recommendations in all areas pertaining to genomic medicine, always in close collaboration with other scientific academic entities, agencies and regulatory bodies.
• Develop, independently or in close collaboration with partner institutions, and coordinate educational activities in the area of genomic medicine. 

Reference:

Cooper DN, et al. (2014). Bridging genomics research between developed and developing countries: The Genomic Medicine Alliance. Per Med 11(7): 615-623.    

* The notion ‘low-resource environments’ is used to specify an environment where: (a) resources assigned for genomics research are scarce, (b) access to genomics knowledge and information is low, (c) implementation of Genomics is limited, (d) genomics education is relatively poor, and (e) collaborative opportunities in genomic research with other institutions are rare for geographical, societal, economic or political reasons.

The following scientific articles have resulted from collaborative work performed by members of the various Working Groups of the Genomic Medicine Alliance and listed below in chronological order:

2013:

Patrinos GP, et al. (2013). Genetic tests obtainable through pharmacies: The good the bad and the ugly. Hum Genomics 7:17.   

2014:

Cooper DN, et al. (2014). Bridging genomics research between developed and developing countries: The Genomic Medicine Alliance. Per Med 11(7): 615-623.  

Dalabira E, et al. (2014). An online resource triangulating drugs with genes and biomarkers for clinical pharmacogenomics. Public Health Genomics 17(5-6): 265-271.

Kechagia S, et al. (2014). Personal Genomics in Greece: An Overview of Available Direct-to-Consumer Genomic Services and the Relevant Legal Framework. Public Health Genomics 17(5-6): 299-305. 

Mitropoulou C, et al. (2014). Documentation and analysis of the policy environment and key stakeholders in pharmacogenomics and genomic medicine in Greece. Public Health Genomics 17(5-6): 280-286.    

Mizzi C, et al. (2014). Personalized pharmacogenomics profiling using whole genome sequencing. Pharmacogenomics, 15(9): 1223-1234. 

Pisanu C, et al. (2014). Assessment of the Pharmacogenomics Educational Environment in Southeast Europe. Public Health Genomics 17(5-6): 272-279.     

Snyder SR, et al. (2014). Economic evaluation of pharmacogenomics: a value-based approach to pragmatic decision making in the face of complexity. Public Health Genomics 17(5-6): 256-264.  

2015:

Karageorgos Ι, et al. (2015). Identification of cancer predisposition variants using a next generation sequencing-based family genomics approach. Hum Genomics. 9: 12.

Mitropoulos K, et al. (2015). Success stories in genomic medicine from resource-limited countries. Hum Genomics 9: 11.

2016:

Mizzi C, et al. (2016). A European spectrum of pharmacogenomic biomarkers: Implications for clinical pharmacogenomics. PLoS One. 11(9): e0162866. 

Vozikis A, et al. (2016). Test Pricing and Reimbursement in Genomic Medicine: Towards a General Strategy. Public Health Genomics 19(6): 352-363. 

2017:

Balasopoulou A, et al. (2017). Advancing Global Precision Medicine: An Overview of Genomic Testing and Counseling Services in Malaysia. OMICS 21(12): 733-740. 

Mitropoulos K, et al. (2017). Genomic Medicine Without Borders: Which Strategies Should Developing Countries Employ to Invest in Precision Medicine? A New "Fast-Second Winner" Strategy. OMICS 21(11): 647-657.

Sarris K, et al. (2017). Application of the DruGeVar Database in Cancer Genomics and Pharmacogenomics. Public Health Genomics 20(2): 142-147.

Viennas E, et al. (2017). Expanded national database collection and data coverage in the FINDbase worldwide database for clinically relevant genomic variation allele frequencies. Nucleic Acids Res 45(D1): D846-D853.