Billions of people globally live in developing countries where infrastructure and regulatory bodies are often lacking and socioeconomic inequality is prevalent. Due to this disparity, people living in these areas may not have access to high quality commodities such as essential medicines, clean water, or even nutritional staples such as milk. At face value, these items appear to be unrelated; however, they actually share the same underlying causes including lack of regulatory oversight, poor laboratory infrastructure, and insufficient funding. Often, these issues tend to go unaddressed which further incentivizes their existence. This is problematic because consumption of substandard medicines, contaminated water, or poor quality milk can lead to a slew of health problems including disease, chronic illness, antibiotic resistance, and even death. The gold standard analytical technologies used to assess the quality of these commodities are often lacking or inaccessible in developing countries. As a result, there is a dire need for low-cost and portable alternative technologies to assess the quality of medicines, water, and milk.At the heart of my work are two powerful analytical tools, paper and yeast. Paper has long been used since ancient times as a platform for chromatography. It is still widely used today in a wide array of point-of-care diagnostics which can detect glucose, fungal pathogens, viral DNA, enzymes, or even antibiotics. Much like paper, yeast are powerful bioanalytical tools. Yeast, specifically S. cerevisiae, are microorganisms which are responsive to a wide range of genetic modifications, thus facilitating the fabrication of different biosensors for clinical, diagnostic, and environmental purposes. Yeast have been engineered to detect heavy metals such as cadmium, fungal pathogens, antibiotics, and environmental estrogens. This work describes the optimization and development of several paper and yeast based devices I created to assess the quality of substandard medicines, milk, and drinking water. With some room for improvement, my hope is that one day these tools can be used in a low-technology or field setting to identify the sources of each problem and prevent their re-occurrence.