<![CDATA[Background. Pharmaceutical packaging plays a crucial role in ensuring drug safety and stability, yet it significantly contributes to environmental degradation due to the extensive use of petroleum-based plastics. Increasing regulatory pressure and global sustainability commitments have intensified the need for environmentally responsible alternatives. Life Cycle Assessment (LCA) offers a comprehensive framework for evaluating the environmental impacts of packaging materials across their entire life cycle. Algae-based biopolymers have emerged as a promising solution due to their renewable origin and biodegradability. This study aims to assess the environmental and functional feasibility of transitioning from conventional polymers to algae-based biopolymers in pharmaceutical packaging. Purpose. A mixed-methods approach was employed, integrating LCA modeling with experimental evaluation of material performance. Representative packaging systems were analyzed using standardized LCA tools to measure global warming potential, energy consumption, water use, and waste generation. Mechanical and barrier properties were tested under controlled laboratory conditions, and comparative analysis was conducted using inferential statistical techniques. Method. Results indicate that algae-based biopolymers significantly reduce carbon emissions, energy use, and waste generation, although they require higher water inputs and exhibit slightly lower mechanical strength. Functional performance remains within acceptable pharmaceutical standards, and environmental improvements are statistically significant. Results. Findings suggest that algae-based biopolymers offer a viable pathway toward sustainable pharmaceutical packaging, balancing environmental benefits with functional requirements.. Conclusion. Representative packaging systems were analyzed using standardized LCA tools to measure global warming potential, energy consumption, water use, and waste generation. Mechanical and barrier properties were tested under controlled laboratory conditions, and comparative analysis was conducted using inferential statistical techniques.]]>
